JOB DESCRIPTION Help shape how intelligent systems are built and delivered at the company. In this role, you'll contribute to the LLM Suite platform by building AI/ML and agentic capabilities that are secure, reliable, and ready for production. You'll collaborate closely with senior engineers, learn through real design discussions, and grow your technical depth across cloud and modern AI frameworks. If you enjoy solving tough problems and iterating quickly with feedback, you'll fit right in. As an Applied AI ML Engineer in LLM Suite Engineering, Senior Associate, you will design, build, and troubleshoot software that enables AI/ML and agentic experiences on the platform. You will write secure, high-quality code and support algorithms that integrate with existing systems. You will collaborate with senior engineers on designs and implementation choices, focusing on reliability and operational stability. You will help deliver GenAI services using public cloud capabilities. You will explore and operationalize emerging patterns such as agent-to-agent communication, model context protocols, and agentic orchestration, turning early-stage concepts into scalable, production-ready capabilities. You will contribute as a team player who seeks and applies feedback. Job Responsibilities Design, develop, and troubleshoot software solutions using creative approaches to solve complex technical challenges Write secure, high-quality production code and maintain algorithms that integrate with existing systems Collaborate with senior engineers and participate in design discussions Build AI/ML solutions and agentic systems for the LLM Suite platform using public cloud architecture (Azure, AWS) and modern agentic frameworks Implement GenAI services leveraging Azure OpenAI models and AWS Bedrock Collaborate openly with the team, seek feedback, and apply it to improve outcomes Required Qualifications, Capabilities, and Skills Computer science degree or equivalent practical experience Hands on experience with system design, application development, testing, and operational stability Strong understanding of the Software Development Life Cycle Preferred Qualifications, Capabilities, and Skills Experience implementing GenAI services leveraging Azure OpenAI models and AWS Bedrock Proficiency in Python (FastAPI) Experience building microservices and APIs Experience with elastic compute, NoSQL databases, and messaging queues Proficiency working with large language models and building agents with LangGraph Experience developing, debugging, and maintaining code in a large corporate environment using modern programming and database querying languages, including containerization Knowledge of agent-to-agent (A2A) communication, Model Context Protocol (MCP), AI skills development, personal AI assistants, or agentic orchestrators ABOUT US the company, one of the oldest financial institutions, offers innovative financial solutions to millions of consumers, small businesses and many of the world's most prominent corporate, institutional and government clients under the J.P. Morgan and Chase brands. Our history spans over 200 years and today we are a leader in investment banking, consumer and small business banking, commercial banking, financial transaction processing and asset management. We recognize that our people are our strength and the diverse talents they bring to our global workforce are directly linked to our success. We are an equal opportunity employer and place a high value on diversity and inclusion at our company. We do not discriminate on the basis of any protected attribute, including race, religion, color, national origin, gender, sexual orientation, gender identity, gender expression, age, marital or veteran status, pregnancy or disability, or any other basis protected under applicable law. We also make reasonable accommodations for applicants' and employees' religious practices and beliefs, as well as mental health or physical disability needs. Visit our FAQs for more information about requesting an accommodation. ABOUT THE TEAM Our Corporate Technology team relies on smart, driven people like you to develop applications and provide tech support for all our corporate functions across our network. Your efforts will touch lives all over the financial spectrum and across all our divisions: Global Finance, Corporate Treasury, Risk Management, Human Resources, Compliance, Legal, and within the Corporate Administrative Office. You'll be part of a team specifically built to meet and exceed our evolving technology needs, as well as our technology controls agenda.
27/07/2026
Full time
JOB DESCRIPTION Help shape how intelligent systems are built and delivered at the company. In this role, you'll contribute to the LLM Suite platform by building AI/ML and agentic capabilities that are secure, reliable, and ready for production. You'll collaborate closely with senior engineers, learn through real design discussions, and grow your technical depth across cloud and modern AI frameworks. If you enjoy solving tough problems and iterating quickly with feedback, you'll fit right in. As an Applied AI ML Engineer in LLM Suite Engineering, Senior Associate, you will design, build, and troubleshoot software that enables AI/ML and agentic experiences on the platform. You will write secure, high-quality code and support algorithms that integrate with existing systems. You will collaborate with senior engineers on designs and implementation choices, focusing on reliability and operational stability. You will help deliver GenAI services using public cloud capabilities. You will explore and operationalize emerging patterns such as agent-to-agent communication, model context protocols, and agentic orchestration, turning early-stage concepts into scalable, production-ready capabilities. You will contribute as a team player who seeks and applies feedback. Job Responsibilities Design, develop, and troubleshoot software solutions using creative approaches to solve complex technical challenges Write secure, high-quality production code and maintain algorithms that integrate with existing systems Collaborate with senior engineers and participate in design discussions Build AI/ML solutions and agentic systems for the LLM Suite platform using public cloud architecture (Azure, AWS) and modern agentic frameworks Implement GenAI services leveraging Azure OpenAI models and AWS Bedrock Collaborate openly with the team, seek feedback, and apply it to improve outcomes Required Qualifications, Capabilities, and Skills Computer science degree or equivalent practical experience Hands on experience with system design, application development, testing, and operational stability Strong understanding of the Software Development Life Cycle Preferred Qualifications, Capabilities, and Skills Experience implementing GenAI services leveraging Azure OpenAI models and AWS Bedrock Proficiency in Python (FastAPI) Experience building microservices and APIs Experience with elastic compute, NoSQL databases, and messaging queues Proficiency working with large language models and building agents with LangGraph Experience developing, debugging, and maintaining code in a large corporate environment using modern programming and database querying languages, including containerization Knowledge of agent-to-agent (A2A) communication, Model Context Protocol (MCP), AI skills development, personal AI assistants, or agentic orchestrators ABOUT US the company, one of the oldest financial institutions, offers innovative financial solutions to millions of consumers, small businesses and many of the world's most prominent corporate, institutional and government clients under the J.P. Morgan and Chase brands. Our history spans over 200 years and today we are a leader in investment banking, consumer and small business banking, commercial banking, financial transaction processing and asset management. We recognize that our people are our strength and the diverse talents they bring to our global workforce are directly linked to our success. We are an equal opportunity employer and place a high value on diversity and inclusion at our company. We do not discriminate on the basis of any protected attribute, including race, religion, color, national origin, gender, sexual orientation, gender identity, gender expression, age, marital or veteran status, pregnancy or disability, or any other basis protected under applicable law. We also make reasonable accommodations for applicants' and employees' religious practices and beliefs, as well as mental health or physical disability needs. Visit our FAQs for more information about requesting an accommodation. ABOUT THE TEAM Our Corporate Technology team relies on smart, driven people like you to develop applications and provide tech support for all our corporate functions across our network. Your efforts will touch lives all over the financial spectrum and across all our divisions: Global Finance, Corporate Treasury, Risk Management, Human Resources, Compliance, Legal, and within the Corporate Administrative Office. You'll be part of a team specifically built to meet and exceed our evolving technology needs, as well as our technology controls agenda.
Senior AI Engineer Manager/Associate Director Capital Markets Location: London Working pattern: Hybrid Salary: Compensation aligned to experience and seniority Ref: J13114 Senior AI Engineering professionals are required to support the design, build and delivery of advanced AI solutions within financial services and capital markets environments. This role would suit an experienced professional with a strong background in AI engineering and enterprise solution delivery within complex environments. You will play a key role in shaping AI strategy, leading teams and delivering enterprise AI solutions, helping organisations solve complex operational, technical and regulatory challenges through AI adoption at scale. You will work across multidisciplinary teams, collaborating with data scientists, architects, MLOps/LLMOps engineers, business stakeholders and senior leadership to design, deliver and scale AI products, agentic AI solutions and data driven applications. Key responsibilities: Building and deploying AI prototypes, products and production ready solutions Designing and implementing end to end AI solutions that integrate with enterprise systems Working with LLMs, prompt engineering, RAG patterns, embeddings and fine tuning Developing AI agents and agentic workflows using modern frameworks Working with vector databases, APIs and modern data platforms Supporting AI deployment, serving patterns, evaluation frameworks and integration design Using Python and SQL to build robust, scalable AI and data solutions Working with cloud platforms such as AWS, Azure, GCP or Databricks Supporting MLOps, LLMOps, CI/CD and software engineering best practice Collaborating with technical and non-technical stakeholders across complex programmes Helping identify technical, delivery, security, data privacy and regulatory risks Contributing to technical documentation, solution design and delivery planning Supporting AI implementation and scaling initiatives across complex environments Leading and developing teams, supporting capability growth through mentoring, coaching and creating a collaborative, high performing environment Experience Required: Strong Python and SQL experience Applied AI engineering, ML engineering or software engineering background Experience with LLMs, RAG, embeddings, prompt engineering or fine tuning Exposure to LangChain, LangGraph, Agent Development Kit or similar agent frameworks Experience with vector databases such as Pinecone, Chroma or similar API development experience, ideally with FastAPI or similar frameworks Knowledge of MLOps, LLMOps, CI/CD or production deployment practices Experience designing or supporting evaluation frameworks for AI or agentic systems Experience working with modern data architectures and cloud platforms Understanding of AI risk, governance, security and regulatory considerations Financial services experience within capital markets or broader banking environments This is a strong opportunity for an AI engineering professional who wants to work on high impact AI and data transformation programmes within complex financial services environments. Alternatively, you can refer a friend or colleague by taking part in our fantastic referral schemes! If you have a friend or colleague who would be interested in this role, please refer them to us. For each relevant candidate that you introduce to us (there is no limit) and we place, you will be entitled to our general gift/voucher scheme. Datatech is one of the UK's leading recruitment agencies in the field of analytics and host of the critically acclaimed event, Women in Data UK. For more information visit our website: (url removed)
27/07/2026
Full time
Senior AI Engineer Manager/Associate Director Capital Markets Location: London Working pattern: Hybrid Salary: Compensation aligned to experience and seniority Ref: J13114 Senior AI Engineering professionals are required to support the design, build and delivery of advanced AI solutions within financial services and capital markets environments. This role would suit an experienced professional with a strong background in AI engineering and enterprise solution delivery within complex environments. You will play a key role in shaping AI strategy, leading teams and delivering enterprise AI solutions, helping organisations solve complex operational, technical and regulatory challenges through AI adoption at scale. You will work across multidisciplinary teams, collaborating with data scientists, architects, MLOps/LLMOps engineers, business stakeholders and senior leadership to design, deliver and scale AI products, agentic AI solutions and data driven applications. Key responsibilities: Building and deploying AI prototypes, products and production ready solutions Designing and implementing end to end AI solutions that integrate with enterprise systems Working with LLMs, prompt engineering, RAG patterns, embeddings and fine tuning Developing AI agents and agentic workflows using modern frameworks Working with vector databases, APIs and modern data platforms Supporting AI deployment, serving patterns, evaluation frameworks and integration design Using Python and SQL to build robust, scalable AI and data solutions Working with cloud platforms such as AWS, Azure, GCP or Databricks Supporting MLOps, LLMOps, CI/CD and software engineering best practice Collaborating with technical and non-technical stakeholders across complex programmes Helping identify technical, delivery, security, data privacy and regulatory risks Contributing to technical documentation, solution design and delivery planning Supporting AI implementation and scaling initiatives across complex environments Leading and developing teams, supporting capability growth through mentoring, coaching and creating a collaborative, high performing environment Experience Required: Strong Python and SQL experience Applied AI engineering, ML engineering or software engineering background Experience with LLMs, RAG, embeddings, prompt engineering or fine tuning Exposure to LangChain, LangGraph, Agent Development Kit or similar agent frameworks Experience with vector databases such as Pinecone, Chroma or similar API development experience, ideally with FastAPI or similar frameworks Knowledge of MLOps, LLMOps, CI/CD or production deployment practices Experience designing or supporting evaluation frameworks for AI or agentic systems Experience working with modern data architectures and cloud platforms Understanding of AI risk, governance, security and regulatory considerations Financial services experience within capital markets or broader banking environments This is a strong opportunity for an AI engineering professional who wants to work on high impact AI and data transformation programmes within complex financial services environments. Alternatively, you can refer a friend or colleague by taking part in our fantastic referral schemes! If you have a friend or colleague who would be interested in this role, please refer them to us. For each relevant candidate that you introduce to us (there is no limit) and we place, you will be entitled to our general gift/voucher scheme. Datatech is one of the UK's leading recruitment agencies in the field of analytics and host of the critically acclaimed event, Women in Data UK. For more information visit our website: (url removed)
United States Digital Space LLC in the United Kingdom seeks an Applied AI ML Lead to shape the future of intelligent systems. You will design and deliver production-grade AI/ML solutions while owning technical direction and collaborating across engineering teams. This role offers opportunities to develop agentic capabilities and contribute to a culture of innovation and learning. Ideal candidates will have a strong technical background in Python and experience with system design and operational stability.
27/07/2026
Full time
United States Digital Space LLC in the United Kingdom seeks an Applied AI ML Lead to shape the future of intelligent systems. You will design and deliver production-grade AI/ML solutions while owning technical direction and collaborating across engineering teams. This role offers opportunities to develop agentic capabilities and contribute to a culture of innovation and learning. Ideal candidates will have a strong technical background in Python and experience with system design and operational stability.
Job Description Build what's next in applied AI at the company - where your work shapes how teams use intelligent systems at scale. You'll lead hands-on engineering for agentic and GenAI capabilities that power the LLM Suite platform. This role offers a mix of deep technical problem-solving, architecture ownership, and collaboration with talented builders. If you enjoy turning ambiguity into reliable production systems, you'll thrive here. Join a team that values craft, security, and learning. As an Applied AI ML Lead in LLM Suite Engineering, you will design and deliver production-grade AI/ML and agentic solutions that integrate seamlessly with existing systems. You will own technical direction across architecture, implementation, and operational stability, with a strong focus on secure, high-quality software. You will partner with peers across engineering to identify patterns and improve standards, reliability, and scalability. You will help evolve the platform using modern public cloud services and agentic frameworks. You will contribute to a collaborative culture through communities of practice and emerging-technology events. You will explore and operationalize emerging patterns such as agent-to-agent communication, model context protocols, and agentic orchestration, turning early-stage concepts into scalable, production-ready capabilities. Job Responsibilities Design, develop, and troubleshoot software solutions using creative approaches to solve complex technical challenges Write secure, high-quality production code and maintain algorithms that integrate with existing systems Create architecture and design artifacts for complex applications, ensuring design constraints are met through delivery Build AI/ML solutions and agentic systems for the LLM Suite platform using public cloud architecture (Azure, AWS) and modern agentic frameworks Implement GenAI services leveraging Azure OpenAI models and AWS Bedrock Identify hidden problems and patterns in data proactively to improve coding standards and system architecture Participate in software engineering communities of practice and events focused on emerging technologies Required Qualifications, Capabilities, and Skills Computer science degree or equivalent practical experience Hands on experience with system design, application development, testing, and operational stability Proficiency in Python (FastAPI) Experience building microservices and APIs Experience with elastic compute, NoSQL databases, and messaging queues Strong understanding of the Software Development Life Cycle Solid grasp of CI/CD, application resiliency, and security Preferred Qualifications, Capabilities, and Skills Experience implementing GenAI services leveraging Azure OpenAI models and AWS Bedrock Proficiency working with large language models and building agents with LangGraph Experience developing, debugging, and maintaining code in a large corporate environment using modern programming and database querying languages Experience with containerization Knowledge of agent to agent (A2A) communication concepts Familiarity with Model Context Protocol (MCP) Experience with agentic orchestrators, personal AI assistants, or AI skills development. We recognize that our people are our strength and the diverse talents they bring to our global workforce are directly linked to our success. We are an equal opportunity employer and place a high value on diversity and inclusion at our company. We do not discriminate on the basis of any protected attribute, including race, religion, color, national origin, gender, sexual orientation, gender identity, gender expression, age, marital or veteran status, pregnancy or disability, or any other basis protected under applicable law. We also make reasonable accommodations for applicants' and employees' religious practices and beliefs, as well as mental health or physical disability needs. Visit our FAQs for more information about requesting an accommodation. About the Team Our Corporate Technology team relies on smart, driven people like you to develop applications and provide tech support for all our corporate functions across our network. Your efforts will touch lives all over the financial spectrum and across all our divisions: Global Finance, Corporate Treasury, Risk Management, Human Resources, Compliance, Legal, and within the Corporate Administrative Office. You'll be part of a team specifically built to meet and exceed our evolving technology needs, as well as our technology controls agenda.
26/07/2026
Full time
Job Description Build what's next in applied AI at the company - where your work shapes how teams use intelligent systems at scale. You'll lead hands-on engineering for agentic and GenAI capabilities that power the LLM Suite platform. This role offers a mix of deep technical problem-solving, architecture ownership, and collaboration with talented builders. If you enjoy turning ambiguity into reliable production systems, you'll thrive here. Join a team that values craft, security, and learning. As an Applied AI ML Lead in LLM Suite Engineering, you will design and deliver production-grade AI/ML and agentic solutions that integrate seamlessly with existing systems. You will own technical direction across architecture, implementation, and operational stability, with a strong focus on secure, high-quality software. You will partner with peers across engineering to identify patterns and improve standards, reliability, and scalability. You will help evolve the platform using modern public cloud services and agentic frameworks. You will contribute to a collaborative culture through communities of practice and emerging-technology events. You will explore and operationalize emerging patterns such as agent-to-agent communication, model context protocols, and agentic orchestration, turning early-stage concepts into scalable, production-ready capabilities. Job Responsibilities Design, develop, and troubleshoot software solutions using creative approaches to solve complex technical challenges Write secure, high-quality production code and maintain algorithms that integrate with existing systems Create architecture and design artifacts for complex applications, ensuring design constraints are met through delivery Build AI/ML solutions and agentic systems for the LLM Suite platform using public cloud architecture (Azure, AWS) and modern agentic frameworks Implement GenAI services leveraging Azure OpenAI models and AWS Bedrock Identify hidden problems and patterns in data proactively to improve coding standards and system architecture Participate in software engineering communities of practice and events focused on emerging technologies Required Qualifications, Capabilities, and Skills Computer science degree or equivalent practical experience Hands on experience with system design, application development, testing, and operational stability Proficiency in Python (FastAPI) Experience building microservices and APIs Experience with elastic compute, NoSQL databases, and messaging queues Strong understanding of the Software Development Life Cycle Solid grasp of CI/CD, application resiliency, and security Preferred Qualifications, Capabilities, and Skills Experience implementing GenAI services leveraging Azure OpenAI models and AWS Bedrock Proficiency working with large language models and building agents with LangGraph Experience developing, debugging, and maintaining code in a large corporate environment using modern programming and database querying languages Experience with containerization Knowledge of agent to agent (A2A) communication concepts Familiarity with Model Context Protocol (MCP) Experience with agentic orchestrators, personal AI assistants, or AI skills development. We recognize that our people are our strength and the diverse talents they bring to our global workforce are directly linked to our success. We are an equal opportunity employer and place a high value on diversity and inclusion at our company. We do not discriminate on the basis of any protected attribute, including race, religion, color, national origin, gender, sexual orientation, gender identity, gender expression, age, marital or veteran status, pregnancy or disability, or any other basis protected under applicable law. We also make reasonable accommodations for applicants' and employees' religious practices and beliefs, as well as mental health or physical disability needs. Visit our FAQs for more information about requesting an accommodation. About the Team Our Corporate Technology team relies on smart, driven people like you to develop applications and provide tech support for all our corporate functions across our network. Your efforts will touch lives all over the financial spectrum and across all our divisions: Global Finance, Corporate Treasury, Risk Management, Human Resources, Compliance, Legal, and within the Corporate Administrative Office. You'll be part of a team specifically built to meet and exceed our evolving technology needs, as well as our technology controls agenda.
Solution Engineer - Consolidated About Neural Concept Engineering is at an inflection point. The teams defining the next generation of aircraft, electric vehicles, and consumer products are not just designing faster. They are designing fundamentally differently, with AI embedded at the core of their workflows. Neural Concept builds the Engineering AI platform that makes this possible. We help the world's leading engineering teams accelerate development, improve product outcomes, and scale engineering capacity, turning months of simulation into days and engineering intuition into data-driven insight. We work with elite engineering teams in Automotive, Aerospace, High-Tech and Electronics, and advanced manufacturing, where the stakes are high, the complexity is rising, and the pressure to innovate has never been greater. We are changing how engineers work. Come build that future with us. About the Role As a Solution Engineer, you sit at the intersection of engineering credibility and strategic influence. You are the person in the room who can connect a VP's business challenge to a concrete, well-scoped AI solution, and who knows Neural Concept's platform and roadmap well enough to make that connection land with confidence. This is not a purely technical role, and it is not a pure sales role. You are a trusted advisor: someone who earns credibility through engineering background and product depth, and who builds long-term account relationships by consistently framing the right problems and the right solutions at the right moment. You drive the full pre-sales motion, from discovery to demo to signed Statement of Work, and you remain the account's technical compass through the client lifecycle, identifying and shaping expansion opportunities. What you will do Position NC as a long-term strategic partner and trusted engineering advisor across engineering teams, managers, and VPs Lead structured discovery sessions to identify where NC creates the most impact, framing use cases that are technically feasible and commercially grounded Define the AI strategy and technical roadmap for each account, translating NC's capabilities and product direction into a multi-horizon vision Create and deliver compelling, client-tailored demos and presentations grounded in the client's engineering workflows, technically credible and aligned with the vision Create and co-own the Statement of Work, with deep understanding of the technical building blocks and how these transform the client's existing workflows Prepare and run Steering Committees, connecting engineering challenges to strategic outcomes Drive user adoption and engagement across technical users, managers, and designers, ensuring NC is embedded in daily workflows and engineering champions emerge Identify upsell and expansion opportunities from account knowledge and commercial signals, and shape them into well-scoped proposals Collaborate with the Sales team to advance and close deals, with the Forward Deployed Engineering team to ensure smooth pre-sales to delivery transitions, and surface client insights to Product and R&D to inform roadmap priorities Who you are You hold an engineering degree (mechanical, aerospace, automotive, industrial, or similar) and have a solid understanding of CAD and CAE workflows, including where bottlenecks lie and what it takes to transform those workflows with AI You are naturally curious and people-driven. You earn trust through genuine interest in client challenges and make engineers and executives feel understood You are proactive and commercially driven. You move accounts forward without being asked, spot opportunities early, and bring structure to ambiguous situations You are a confident challenger. You ask uncomfortable questions, reframe assumptions, and guide clients toward better outcomes even when it requires pushing back You are an outstanding communicator: you own executive conversations, drive narrative with clarity, and connect engineering problems to strategic outcomes You understand AI and machine learning applied to engineering at a conceptual level, and are comfortable creating demos and prototypes using AI-assisted tools with working knowledge of Python and modern development practices You have experience in a client-facing role: pre-sales, solutions consulting, technical account management, or engineering consulting You are fluent in English Add other language requirements depending on region What Will Set You Apart You have deep, hands-on simulation experience: full pipelines from CAD to post-processing, solver experience, and workflow automation You are a strong programmer: you write clean Python, build data pipelines, and are comfortable in ML-DL frameworks including model training, evaluation, and deployment You can go deep in technical discovery: dive into customer toolchains, data environments, and simulation setups to assess feasibility at the level a simulation engineer would respect You can build end-to-end engineering workflow demos from scratch, rapidly prototyping the full arc from design generation and simulation to data pipelines, model training, and application deployment using agentic development tools Nice-to-Have Strategic or technical consulting background, executing digital transformations Previous experience working in engineering software companies or using engineering software tools (e.g., Ansys, Altair, Siemens, Dassault Systèmes, or Autodesk) Background in ML-DL research or development in an engineering context Experience automating CAE workflows (scripting, batch processing, surrogate model pipelines) What You Get Work with a world-class technology team - our engineers are top-notch, and we always aim for excellence. Benefit from a competitive salary and rewarding opportunities as we continue to scale. Thrive in a collaborative, multicultural environment where your work is visible and recognized. Develop professionally alongside talented colleagues who share knowledge freely and support one another. Make a global impact by helping customers shift to AI-assisted design, making innovation faster, smarter, and more sustainable. Balance life and work with a hybrid model and flexible hours-we care about results, not rigid schedules. Where You Will Be Based in the UK (Midlands preferred, with flexibility) 30% travel required (UK & EMEA) We're proud to be an equal opportunity employer, and we're committed to building a diverse and inclusive environment where you can thrive.
26/07/2026
Full time
Solution Engineer - Consolidated About Neural Concept Engineering is at an inflection point. The teams defining the next generation of aircraft, electric vehicles, and consumer products are not just designing faster. They are designing fundamentally differently, with AI embedded at the core of their workflows. Neural Concept builds the Engineering AI platform that makes this possible. We help the world's leading engineering teams accelerate development, improve product outcomes, and scale engineering capacity, turning months of simulation into days and engineering intuition into data-driven insight. We work with elite engineering teams in Automotive, Aerospace, High-Tech and Electronics, and advanced manufacturing, where the stakes are high, the complexity is rising, and the pressure to innovate has never been greater. We are changing how engineers work. Come build that future with us. About the Role As a Solution Engineer, you sit at the intersection of engineering credibility and strategic influence. You are the person in the room who can connect a VP's business challenge to a concrete, well-scoped AI solution, and who knows Neural Concept's platform and roadmap well enough to make that connection land with confidence. This is not a purely technical role, and it is not a pure sales role. You are a trusted advisor: someone who earns credibility through engineering background and product depth, and who builds long-term account relationships by consistently framing the right problems and the right solutions at the right moment. You drive the full pre-sales motion, from discovery to demo to signed Statement of Work, and you remain the account's technical compass through the client lifecycle, identifying and shaping expansion opportunities. What you will do Position NC as a long-term strategic partner and trusted engineering advisor across engineering teams, managers, and VPs Lead structured discovery sessions to identify where NC creates the most impact, framing use cases that are technically feasible and commercially grounded Define the AI strategy and technical roadmap for each account, translating NC's capabilities and product direction into a multi-horizon vision Create and deliver compelling, client-tailored demos and presentations grounded in the client's engineering workflows, technically credible and aligned with the vision Create and co-own the Statement of Work, with deep understanding of the technical building blocks and how these transform the client's existing workflows Prepare and run Steering Committees, connecting engineering challenges to strategic outcomes Drive user adoption and engagement across technical users, managers, and designers, ensuring NC is embedded in daily workflows and engineering champions emerge Identify upsell and expansion opportunities from account knowledge and commercial signals, and shape them into well-scoped proposals Collaborate with the Sales team to advance and close deals, with the Forward Deployed Engineering team to ensure smooth pre-sales to delivery transitions, and surface client insights to Product and R&D to inform roadmap priorities Who you are You hold an engineering degree (mechanical, aerospace, automotive, industrial, or similar) and have a solid understanding of CAD and CAE workflows, including where bottlenecks lie and what it takes to transform those workflows with AI You are naturally curious and people-driven. You earn trust through genuine interest in client challenges and make engineers and executives feel understood You are proactive and commercially driven. You move accounts forward without being asked, spot opportunities early, and bring structure to ambiguous situations You are a confident challenger. You ask uncomfortable questions, reframe assumptions, and guide clients toward better outcomes even when it requires pushing back You are an outstanding communicator: you own executive conversations, drive narrative with clarity, and connect engineering problems to strategic outcomes You understand AI and machine learning applied to engineering at a conceptual level, and are comfortable creating demos and prototypes using AI-assisted tools with working knowledge of Python and modern development practices You have experience in a client-facing role: pre-sales, solutions consulting, technical account management, or engineering consulting You are fluent in English Add other language requirements depending on region What Will Set You Apart You have deep, hands-on simulation experience: full pipelines from CAD to post-processing, solver experience, and workflow automation You are a strong programmer: you write clean Python, build data pipelines, and are comfortable in ML-DL frameworks including model training, evaluation, and deployment You can go deep in technical discovery: dive into customer toolchains, data environments, and simulation setups to assess feasibility at the level a simulation engineer would respect You can build end-to-end engineering workflow demos from scratch, rapidly prototyping the full arc from design generation and simulation to data pipelines, model training, and application deployment using agentic development tools Nice-to-Have Strategic or technical consulting background, executing digital transformations Previous experience working in engineering software companies or using engineering software tools (e.g., Ansys, Altair, Siemens, Dassault Systèmes, or Autodesk) Background in ML-DL research or development in an engineering context Experience automating CAE workflows (scripting, batch processing, surrogate model pipelines) What You Get Work with a world-class technology team - our engineers are top-notch, and we always aim for excellence. Benefit from a competitive salary and rewarding opportunities as we continue to scale. Thrive in a collaborative, multicultural environment where your work is visible and recognized. Develop professionally alongside talented colleagues who share knowledge freely and support one another. Make a global impact by helping customers shift to AI-assisted design, making innovation faster, smarter, and more sustainable. Balance life and work with a hybrid model and flexible hours-we care about results, not rigid schedules. Where You Will Be Based in the UK (Midlands preferred, with flexibility) 30% travel required (UK & EMEA) We're proud to be an equal opportunity employer, and we're committed to building a diverse and inclusive environment where you can thrive.
About the team Elsevier's mission is to help researchers, clinicians, and life sciences professionals advance discovery and improve health outcomes through trusted content, data, and analytics. This role sits within Elsevier's Platform Data Science organization, a centralized AI and data science group responsible for advancing intelligent discovery, retrieval, and generative AI capabilities across Elsevier products and platforms. The organization develops foundational AI technologies that power experiences such as LeapSpace, Elsevier's AI powered research assistant, as well as Elsevier's broader Search & AI Platform. The Platform Data Science organization works at the intersection of: Search and retrieval systems, Generative AI and LLM applications, AI evaluation and experimentation, Semantic enrichment and knowledge systems, Scalable AI platforms and intelligent workflows. About the role We are looking for a Data Scientist III to help design, build, and evaluate advanced AI capabilities supporting LeapSpace and Elsevier's Search & AI Platform initiatives. This role focuses on applied AI development, retrieval systems, and AI evaluation, helping bring cutting edge AI technologies into production experiences used by researchers worldwide. You will work closely with senior data scientists, engineers, product managers, and domain experts across retrieval systems, generative AI, reasoning workflows, evaluation frameworks, and experimentation, contributing to the next generation of AI powered scientific discovery tools. This role is ideal for someone with hands on experience in applied AI, NLP, information retrieval, and LLM based applications, who enjoys building innovative solutions and translating emerging AI techniques into impactful product capabilities. Key responsibilities Develop and improve LLM powered research workflows, including: Scientific question answering, Literature summarization, Semantic exploration and discovery, Research insight generation, Citation aware retrieval and reasoning workflows. Build and iterate on agentic and multi step AI workflows using frameworks such as LangGraph and related orchestration tools. Apply modern techniques in NLP, Generative AI, Embeddings and semantic representations, Retrieval augmented generation (RAG), AI reasoning and workflow orchestration. Evaluate emerging AI models, tools, and frameworks and contribute recommendations for experimentation and adoption. Contribute to prompt engineering, grounding strategies, context management, and hallucination mitigation efforts. Support integration of scientific metadata, ontologies, and knowledge assets into AI powered workflows. Design, develop, and optimize search and retrieval pipelines, including lexical, vector, and hybrid retrieval approaches. Contribute to the development and enhancement of RAG systems that integrate LLMs with trusted scientific and biomedical content. Experiment with embeddings, re ranking models, chunking strategies, and retrieval orchestration techniques to improve relevance and answer quality. Support development of semantic search, ranking, and knowledge discovery capabilities. Collaborate with engineering teams to deploy and scale AI powered solutions. Develop and apply evaluation frameworks for search and AI systems, including IR metrics (e.g., NDCG, recall, precision) and LLM and RAG evaluation metrics (e.g., grounding, faithfulness, hallucination detection). Build and maintain evaluation datasets, benchmark suites, and annotation workflows. Conduct offline experiments and contribute to online experimentation and A/B testing. Analyze experimental results and communicate findings to stakeholders. Contribute to responsible AI practices focused on quality, reliability, and trust. Partner with product managers, engineers, UX researchers, and domain experts to deliver AI powered capabilities. Communicate technical findings and recommendations clearly to both technical and non technical audiences. Contribute to knowledge sharing and adoption of best practices across the Platform Data Science organization. Support delivery of projects from research and experimentation through production deployment. Required qualifications Master's or PhD in Computer Science, Data Science, Machine Learning, NLP, Information Retrieval, or a related field. Experience in data science, machine learning, applied NLP, information retrieval, generative AI, or a related field. Hands on experience with LLM based applications and generative AI systems, RAG pipelines and retrieval systems, Search and retrieval architectures (lexical, vector, hybrid). Evaluation methodologies for IR and generative AI systems. Strong programming skills in Python. Experience with modern AI/ML frameworks and tooling (e.g., PyTorch, Hugging Face, LangChain, LangGraph, Haystack). Experience working with Databricks or similar distributed data and machine learning platforms. Understanding of experimentation methodologies, evaluation frameworks, and statistical analysis. Proficiency with data visualization and analytical tooling (e.g., Tableau, Power BI, matplotlib, seaborn). Demonstrated ability to independently execute technical projects and contribute to cross functional initiatives. Preferred qualifications Experience building AI assistants, agentic workflows, or conversational AI applications. Experience working on search, ranking, recommendation, or retrieval systems. Familiarity with scientific, biomedical, or scholarly datasets. Experience with knowledge graphs, ontologies, or semantic enrichment systems. Exposure to production ML systems and MLOps practices. Academic or industry research experience in NLP, information retrieval, search, or generative AI. Experience working in content rich, knowledge intensive, or highly regulated domains. Working for you - we know that your well being and happiness are key to a long and successful career. Benefits we are delighted to offer Comprehensive Pension Plan. Home, office, or commuting allowance. Generous vacation entitlement and option for sabbatical leave. Maternity, Paternity, Adoption and Family Care leave. Flexible working hours. Personal Choice budget. Internal communities and networks. Various employee discounts. Recruitment introduction reward. Employee Assistance Program (global). About the business As a global leader in information and analytics, we help researchers and healthcare professionals advance science and improve health outcomes for the benefit of society. Building on our publishing heritage, we combine quality information and vast data sets with analytics to support visionary science and research, health education, and interactive learning, as well as exceptional healthcare and clinical practice. At Elsevier, your work contributes to the world's grand challenges and a more sustainable future. We harness innovative technologies to support science and healthcare to partner for a better world. We know your well being and happiness are key to a long and successful career. We are delighted to offer country specific benefits. Click here to access benefits specific to your location. We are committed to providing a fair and accessible hiring process. If you have a disability or other need that requires accommodation or adjustment, please let us know by completing our Applicant Request Support Form or please contact 1-. We are an equal opportunity employer: qualified applicants are considered for and treated during employment without regard to race, color, creed, religion, sex, national origin, citizenship status, disability status, protected veteran status, age, marital status, sexual orientation, gender identity, genetic information, or any other characteristic protected by law. USA Job Seekers: EEO Know Your Rights. Elsevier is a global leader in advanced information and decision support for science and healthcare. We believe that by working together with the communities we serve, we can shape human progress to go further, happen faster, and benefit all. We support continuous discovery and uphold the highest standards of content integrity, reliability, and reproducibility so the communities we serve can advance their field of science, healthcare or innovation with confidence. By combining high quality content with powerful analytics, we transform complexity into clarity and deliver mission critical insights that help professionals make better decisions when it matters most. We deliver insights that help research institutions, governments, and funders achieve their goals. We help researchers discover and share knowledge, collaborate, and accelerate innovation. We help librarians provide verified, quality information to universities. We help innovators turn knowledge into new products. We help health professionals improve patient care and educators train the next generation of doctors and nurses. Connecting quality content and innovative technologies, we make progress go further and happen faster. And by championing inclusion and sustainability, we ensure progress benefits all. With 9,500 employees, over 2,300 technologists in 5 major tech hubs, and more than 60 locations across the globe, we are committed to supporting the scientific and healthcare communities around the world. We offer a diverse range of opportunities across technology, commercial, business, and early career jobs. If you are looking for a career that inspires progress in science . click apply for full job details
26/07/2026
Full time
About the team Elsevier's mission is to help researchers, clinicians, and life sciences professionals advance discovery and improve health outcomes through trusted content, data, and analytics. This role sits within Elsevier's Platform Data Science organization, a centralized AI and data science group responsible for advancing intelligent discovery, retrieval, and generative AI capabilities across Elsevier products and platforms. The organization develops foundational AI technologies that power experiences such as LeapSpace, Elsevier's AI powered research assistant, as well as Elsevier's broader Search & AI Platform. The Platform Data Science organization works at the intersection of: Search and retrieval systems, Generative AI and LLM applications, AI evaluation and experimentation, Semantic enrichment and knowledge systems, Scalable AI platforms and intelligent workflows. About the role We are looking for a Data Scientist III to help design, build, and evaluate advanced AI capabilities supporting LeapSpace and Elsevier's Search & AI Platform initiatives. This role focuses on applied AI development, retrieval systems, and AI evaluation, helping bring cutting edge AI technologies into production experiences used by researchers worldwide. You will work closely with senior data scientists, engineers, product managers, and domain experts across retrieval systems, generative AI, reasoning workflows, evaluation frameworks, and experimentation, contributing to the next generation of AI powered scientific discovery tools. This role is ideal for someone with hands on experience in applied AI, NLP, information retrieval, and LLM based applications, who enjoys building innovative solutions and translating emerging AI techniques into impactful product capabilities. Key responsibilities Develop and improve LLM powered research workflows, including: Scientific question answering, Literature summarization, Semantic exploration and discovery, Research insight generation, Citation aware retrieval and reasoning workflows. Build and iterate on agentic and multi step AI workflows using frameworks such as LangGraph and related orchestration tools. Apply modern techniques in NLP, Generative AI, Embeddings and semantic representations, Retrieval augmented generation (RAG), AI reasoning and workflow orchestration. Evaluate emerging AI models, tools, and frameworks and contribute recommendations for experimentation and adoption. Contribute to prompt engineering, grounding strategies, context management, and hallucination mitigation efforts. Support integration of scientific metadata, ontologies, and knowledge assets into AI powered workflows. Design, develop, and optimize search and retrieval pipelines, including lexical, vector, and hybrid retrieval approaches. Contribute to the development and enhancement of RAG systems that integrate LLMs with trusted scientific and biomedical content. Experiment with embeddings, re ranking models, chunking strategies, and retrieval orchestration techniques to improve relevance and answer quality. Support development of semantic search, ranking, and knowledge discovery capabilities. Collaborate with engineering teams to deploy and scale AI powered solutions. Develop and apply evaluation frameworks for search and AI systems, including IR metrics (e.g., NDCG, recall, precision) and LLM and RAG evaluation metrics (e.g., grounding, faithfulness, hallucination detection). Build and maintain evaluation datasets, benchmark suites, and annotation workflows. Conduct offline experiments and contribute to online experimentation and A/B testing. Analyze experimental results and communicate findings to stakeholders. Contribute to responsible AI practices focused on quality, reliability, and trust. Partner with product managers, engineers, UX researchers, and domain experts to deliver AI powered capabilities. Communicate technical findings and recommendations clearly to both technical and non technical audiences. Contribute to knowledge sharing and adoption of best practices across the Platform Data Science organization. Support delivery of projects from research and experimentation through production deployment. Required qualifications Master's or PhD in Computer Science, Data Science, Machine Learning, NLP, Information Retrieval, or a related field. Experience in data science, machine learning, applied NLP, information retrieval, generative AI, or a related field. Hands on experience with LLM based applications and generative AI systems, RAG pipelines and retrieval systems, Search and retrieval architectures (lexical, vector, hybrid). Evaluation methodologies for IR and generative AI systems. Strong programming skills in Python. Experience with modern AI/ML frameworks and tooling (e.g., PyTorch, Hugging Face, LangChain, LangGraph, Haystack). Experience working with Databricks or similar distributed data and machine learning platforms. Understanding of experimentation methodologies, evaluation frameworks, and statistical analysis. Proficiency with data visualization and analytical tooling (e.g., Tableau, Power BI, matplotlib, seaborn). Demonstrated ability to independently execute technical projects and contribute to cross functional initiatives. Preferred qualifications Experience building AI assistants, agentic workflows, or conversational AI applications. Experience working on search, ranking, recommendation, or retrieval systems. Familiarity with scientific, biomedical, or scholarly datasets. Experience with knowledge graphs, ontologies, or semantic enrichment systems. Exposure to production ML systems and MLOps practices. Academic or industry research experience in NLP, information retrieval, search, or generative AI. Experience working in content rich, knowledge intensive, or highly regulated domains. Working for you - we know that your well being and happiness are key to a long and successful career. Benefits we are delighted to offer Comprehensive Pension Plan. Home, office, or commuting allowance. Generous vacation entitlement and option for sabbatical leave. Maternity, Paternity, Adoption and Family Care leave. Flexible working hours. Personal Choice budget. Internal communities and networks. Various employee discounts. Recruitment introduction reward. Employee Assistance Program (global). About the business As a global leader in information and analytics, we help researchers and healthcare professionals advance science and improve health outcomes for the benefit of society. Building on our publishing heritage, we combine quality information and vast data sets with analytics to support visionary science and research, health education, and interactive learning, as well as exceptional healthcare and clinical practice. At Elsevier, your work contributes to the world's grand challenges and a more sustainable future. We harness innovative technologies to support science and healthcare to partner for a better world. We know your well being and happiness are key to a long and successful career. We are delighted to offer country specific benefits. Click here to access benefits specific to your location. We are committed to providing a fair and accessible hiring process. If you have a disability or other need that requires accommodation or adjustment, please let us know by completing our Applicant Request Support Form or please contact 1-. We are an equal opportunity employer: qualified applicants are considered for and treated during employment without regard to race, color, creed, religion, sex, national origin, citizenship status, disability status, protected veteran status, age, marital status, sexual orientation, gender identity, genetic information, or any other characteristic protected by law. USA Job Seekers: EEO Know Your Rights. Elsevier is a global leader in advanced information and decision support for science and healthcare. We believe that by working together with the communities we serve, we can shape human progress to go further, happen faster, and benefit all. We support continuous discovery and uphold the highest standards of content integrity, reliability, and reproducibility so the communities we serve can advance their field of science, healthcare or innovation with confidence. By combining high quality content with powerful analytics, we transform complexity into clarity and deliver mission critical insights that help professionals make better decisions when it matters most. We deliver insights that help research institutions, governments, and funders achieve their goals. We help researchers discover and share knowledge, collaborate, and accelerate innovation. We help librarians provide verified, quality information to universities. We help innovators turn knowledge into new products. We help health professionals improve patient care and educators train the next generation of doctors and nurses. Connecting quality content and innovative technologies, we make progress go further and happen faster. And by championing inclusion and sustainability, we ensure progress benefits all. With 9,500 employees, over 2,300 technologists in 5 major tech hubs, and more than 60 locations across the globe, we are committed to supporting the scientific and healthcare communities around the world. We offer a diverse range of opportunities across technology, commercial, business, and early career jobs. If you are looking for a career that inspires progress in science . click apply for full job details
Senior / Staff Machine Learning Scientist About Chemify: Chemify is revolutionising chemistry. We are creating a future where the synthesis of previously unimaginable molecules, drugs, and materials is instantly accessible. By combining AI, robotics, and the world's largest continually expanding database of chemical programs, we are accelerating chemical discovery to improve quality of life and extend the reach of humanity. Our Chemifarm facility in Glasgow operates a growing fleet of advanced robotic systems that automate synthesis, optimisation, and library generation. This gives our computational scientists something rare: a direct, high-throughput bridge from in silico design to physically synthesised molecules, closing the design-make-test loop at a pace conventional drug discovery organisations cannot match. Location: Glasgow (onsite, full-time) or fully remote with regular travel to our Glasgow HQ / Chemifarm The Role We are seeking a Senior / Staff Machine Learning Scientist to work across the breadth of Chemify's platform - generative models for chemistry, search and planning for retrosynthesis, computer vision for telemetry from our robotic systems, and agentic workflows that tie it all together. You will partner with computational chemists, CADD scientists, software engineers, and hardware engineers, and apply AI/ML to build the next generation of Chemify's platform. What sets this role apart is the combination of breadth of ML problems - generative chemistry, vision, search, agents - paired with a robotic platform that turns your models into physical experiments. If working across a wide range of hard ML problems on a real-world platform sounds like the right shape of job for you, we'd love to welcome you to our team. Key Responsibilities Build generative and foundation chemistry models for molecular design. Advance retrosynthesis and synthesis aware ML by leveraging Chemify's reaction database and robot execution data. Apply computer vision to transform robot telemetry into models that monitor process state and feedback into experimental control. Prototype agentic workflows that orchestrate models, tools, and the platform - closing loops between proposal, execution, observation, and learning. Productionise models into a reproducible, API first toolkit; partner with Infrastructure on GPU training and HPC; maintain high standards of ML best practices, including rigorous evaluation, benchmarks, and reproducibility. Mentor junior ML scientists, partner with the Head of Advanced Machine Learning on hiring and growth, and represent Chemify's AI/ML capability externally. (Staff level) Set technical direction across the AI/ML stack; lead cross cutting initiatives spanning chemistry models, retrosynthesis, vision, and agents. About You You are an experienced ML scientist who is equally comfortable training models and shipping the code that other people end up building on. You care about whether your model changes a real decision - not just whether it beats a benchmark. You're at home moving across problem types, from generative models to vision to search. We expect you to bring: PhD or equivalent experience in Machine Learning, Computer Science, Statistics, Physics, or a related quantitative field - 5+ years (Senior) or 8+ years (Staff) of hands on applied ML experience, including production grade work. Deep familiarity with modern deep learning stack (PyTorch or JAX), and breadth across at least two of: generative models (diffusion, autoregressive, flow based), graph and equivariant networks, vision (CNNs, ViTs, multimodal LLMs), search and planning (MCTS, A ), or agentic / RL systems. Experience taking ML from prototype to production: reproducible pipelines, distributed jobs, and batch workflows on cloud (AWS / GCP / Azure) or HPC. Strong scientific computing instincts: clean Python, careful experiment design, leakage aware splits, and rigorous benchmarks. Clear communication with non ML scientists and engineers and a willingness to pick up new domains (you don't need to know chemistry on day one). (Staff level) A track record of technical leadership: mentoring, setting standards, and influencing scientific and technical direction beyond your own projects. Beneficial Skills Practical experience with active learning, Bayesian optimisation, conformal prediction, or uncertainty quantification in iterative real world loops. Familiarity with retrosynthesis ML, computer aided synthesis planning (CASP), or reaction condition / yield prediction. Working knowledge of how ML fits into a drug discovery or materials design workflow, plus familiarity with cheminformatics tooling (e.g. RDKit, OpenEye) - or willingness to pick these up. MLOps fluency: experiment tracking, data versioning, model serving, and observability of deployed models. A visible track record in the field - peer reviewed publications, open source contributions, or public projects that demonstrate your judgement on real ML problems. Why Join Chemify? Impact: Your models will directly shape what Chemify's robotic platform proposes, plans, and observes - at a company uniquely positioned to close the loop between design and physical experiment. Autonomy: Reporting to the Head of Advanced Machine Learning, you will work across the AI/ML problems with the most impact, and have meaningful influence over the direction of our AI/ML capability. Ambition: We are a Series B deep tech company investing in world class infrastructure and tackling problems at the frontier of AI, robotics, and chemistry. You will have the resources and the mandate to do AI/ML in a way that isn't possible elsewhere - across chemistry, vision, search, and autonomous systems on the same platform. Advanced Research Centre, University of Glasgow, 11 Chapel Lane, G11 6EW Department Design Retro & Advanced ML Job Title Senior / Staff Machine Learning Scientist
26/07/2026
Full time
Senior / Staff Machine Learning Scientist About Chemify: Chemify is revolutionising chemistry. We are creating a future where the synthesis of previously unimaginable molecules, drugs, and materials is instantly accessible. By combining AI, robotics, and the world's largest continually expanding database of chemical programs, we are accelerating chemical discovery to improve quality of life and extend the reach of humanity. Our Chemifarm facility in Glasgow operates a growing fleet of advanced robotic systems that automate synthesis, optimisation, and library generation. This gives our computational scientists something rare: a direct, high-throughput bridge from in silico design to physically synthesised molecules, closing the design-make-test loop at a pace conventional drug discovery organisations cannot match. Location: Glasgow (onsite, full-time) or fully remote with regular travel to our Glasgow HQ / Chemifarm The Role We are seeking a Senior / Staff Machine Learning Scientist to work across the breadth of Chemify's platform - generative models for chemistry, search and planning for retrosynthesis, computer vision for telemetry from our robotic systems, and agentic workflows that tie it all together. You will partner with computational chemists, CADD scientists, software engineers, and hardware engineers, and apply AI/ML to build the next generation of Chemify's platform. What sets this role apart is the combination of breadth of ML problems - generative chemistry, vision, search, agents - paired with a robotic platform that turns your models into physical experiments. If working across a wide range of hard ML problems on a real-world platform sounds like the right shape of job for you, we'd love to welcome you to our team. Key Responsibilities Build generative and foundation chemistry models for molecular design. Advance retrosynthesis and synthesis aware ML by leveraging Chemify's reaction database and robot execution data. Apply computer vision to transform robot telemetry into models that monitor process state and feedback into experimental control. Prototype agentic workflows that orchestrate models, tools, and the platform - closing loops between proposal, execution, observation, and learning. Productionise models into a reproducible, API first toolkit; partner with Infrastructure on GPU training and HPC; maintain high standards of ML best practices, including rigorous evaluation, benchmarks, and reproducibility. Mentor junior ML scientists, partner with the Head of Advanced Machine Learning on hiring and growth, and represent Chemify's AI/ML capability externally. (Staff level) Set technical direction across the AI/ML stack; lead cross cutting initiatives spanning chemistry models, retrosynthesis, vision, and agents. About You You are an experienced ML scientist who is equally comfortable training models and shipping the code that other people end up building on. You care about whether your model changes a real decision - not just whether it beats a benchmark. You're at home moving across problem types, from generative models to vision to search. We expect you to bring: PhD or equivalent experience in Machine Learning, Computer Science, Statistics, Physics, or a related quantitative field - 5+ years (Senior) or 8+ years (Staff) of hands on applied ML experience, including production grade work. Deep familiarity with modern deep learning stack (PyTorch or JAX), and breadth across at least two of: generative models (diffusion, autoregressive, flow based), graph and equivariant networks, vision (CNNs, ViTs, multimodal LLMs), search and planning (MCTS, A ), or agentic / RL systems. Experience taking ML from prototype to production: reproducible pipelines, distributed jobs, and batch workflows on cloud (AWS / GCP / Azure) or HPC. Strong scientific computing instincts: clean Python, careful experiment design, leakage aware splits, and rigorous benchmarks. Clear communication with non ML scientists and engineers and a willingness to pick up new domains (you don't need to know chemistry on day one). (Staff level) A track record of technical leadership: mentoring, setting standards, and influencing scientific and technical direction beyond your own projects. Beneficial Skills Practical experience with active learning, Bayesian optimisation, conformal prediction, or uncertainty quantification in iterative real world loops. Familiarity with retrosynthesis ML, computer aided synthesis planning (CASP), or reaction condition / yield prediction. Working knowledge of how ML fits into a drug discovery or materials design workflow, plus familiarity with cheminformatics tooling (e.g. RDKit, OpenEye) - or willingness to pick these up. MLOps fluency: experiment tracking, data versioning, model serving, and observability of deployed models. A visible track record in the field - peer reviewed publications, open source contributions, or public projects that demonstrate your judgement on real ML problems. Why Join Chemify? Impact: Your models will directly shape what Chemify's robotic platform proposes, plans, and observes - at a company uniquely positioned to close the loop between design and physical experiment. Autonomy: Reporting to the Head of Advanced Machine Learning, you will work across the AI/ML problems with the most impact, and have meaningful influence over the direction of our AI/ML capability. Ambition: We are a Series B deep tech company investing in world class infrastructure and tackling problems at the frontier of AI, robotics, and chemistry. You will have the resources and the mandate to do AI/ML in a way that isn't possible elsewhere - across chemistry, vision, search, and autonomous systems on the same platform. Advanced Research Centre, University of Glasgow, 11 Chapel Lane, G11 6EW Department Design Retro & Advanced ML Job Title Senior / Staff Machine Learning Scientist
Birmingham, United Kingdom / Brighton, United Kingdom / Bristol, United Kingdom / Cardiff, United Kingdom / Glasgow, United Kingdom / London, United Kingdom / Manchester, United Kingdom / Newcastle Upon Tyne, United Kingdom Location/s: London, Cardiff, Bristol, Brighton, Birmingham, Manchester, Glasgow, Newcastle Relocation supported:Not supported, but internal applications are welcome Hiring manager contact: Sam Ahdab Mott MacDonald is a global engineering, management, and development consultancy with over 20,000 employees across more than 50 countries and 140+ offices. We work across incredible global industries, delivering exciting work that is defining our future and making an important societal impact in the communities we serve. Our people power our performance - we succeed when they do. With countless opportunities to collaborate, learn, and grow, the possibilities for excellence are as varied as every individual. Whether you want to grow as a subject matter expert or broaden your experience with roles across our international community, you're surrounded by global specialists who want to combine their expertise and champion you to be your best. As a proudly employee owned business, we benefit our clients, our communities, and each other, investing in creating the right space for everyone to feel empowered, included, and valued. Whatever your ambition, Mott MacDonald is where people come to be brilliant. Overview of the role: We are looking for a Principal Data Scientist to help shape the design, development and delivery of production grade AI, machine learning and data science solutions across Mott MacDonald. The role will focus on turning complex business, engineering and environmental needs into scalable, reliable data products and AI services. The successful candidate will bring technical experience across generative AI, large language models, retrieval augmented generation, machine learning, computer vision, geospatial data science and MLOps. They will work with multidisciplinary teams to identify valuable use cases, shape solution architecture, develop reliable models and ensure solutions are tested, monitored and improved in live use. The role includes end to end AI and data science delivery; setting standards for model development, evaluation and deployment; building reusable internal AI services; coaching data scientists and engineers; contributing to AI governance; and translating technical opportunities into clear business value for project teams and senior stakeholders. Candidate Specifications: Experience delivering production data science, machine learning or AI in an enterprise environment. Practical experience in Python and modern machine learning frameworks such as PyTorch, TensorFlow or Keras. Practical experience with generative AI, large language models, embedding models, retrieval augmented generation, AI agents, model evaluation and fine tuning techniques. Experience designing and operating end to end MLOps workflows, including model training, deployment, monitoring, automation and continuous improvement. Ability to work across cloud and engineering environments, including tools such as Azure, Kubernetes, Docker, MLflow, GitHub Actions, Terraform or Databricks. Clear communication and stakeholder engagement skills, with the ability to explain complex technical concepts in accessible business language. Experience coaching, mentoring or giving technical guidance to data scientists, machine learning engineers or data professionals Experience applying computer vision, geospatial data science or predictive modelling to engineering, infrastructure, environmental or asset management work. Knowledge of tools and methods such as LangChain, LLM orchestration, agentic tool use, segmentation foundation models, zero/few shot visual understanding Experience developing reusable internal AI platforms, foundation model services or automation capabilities for use by wider teams. Postgraduate qualification or equivalent research experience in data science, engineering, computer science, applied mathematics or a related discipline. Evidence of innovation, publication, award recognition or contribution to data science practice. UK Immigration Mott MacDonald Ltd. are not currently offering sponsorship to candidates under the Skilled Worker visa route in the UK. This decision is as a consequence of the changes made to the Skilled Worker route by the UK Government in April 2024. We continue to welcome applications from candidates who are eligible for alternative immigration routes in the UK, that do not require sponsorship as a Skilled Worker now or in future. At Mott MacDonald, we believe it makes business sense for you and your manager to choose how you can work most effectively to meet your client, team, and personal commitments. We offer a hybrid working policy that embraces your well being, flexibility, and trust. Equality, diversity, and inclusion We put equality, diversity, and inclusion at the heart of our business, seeking to promote fair employment procedures and practices to ensure equal opportunities for all. We encourage individual expression in our workplace and are committed to creating an inclusive environment where everyone feels they can contribute. Accessibility We want you to perform your best at every stage in the recruitment process. If you are disabled or need any support to enable you to apply or attend an interview, please contact us at and we will talk to you about how we can support you. Financial wellbeing We match employee pension contributions between 4.5% and 7%. Life assurance equal up to 4 x your basic salary, with an option to increase the level of cover to 6 x your salary. Our income protection scheme provides a financial benefit, as well as absence and return to work support due to long term illness or injury. Flexible benefits, including increased life assurance cover, critical illness insurance, payroll saving and will writing. As an independently owned business we share the financial success of the business with all our colleagues in various ways including annual bonus schemes. Employee Ownership Our employee ownership model means no external investors, just us, creating a culture of shared success. Our employees have a stake and a voice in our business, giving them a direct connection to our success through our personal and group performance bonuses. As your career grows, so does your stake, recognising your long term impact and contribution. Your voice matters, with the opportunity to connect directly with senior leadership through formal channels to help shape our future. For our senior roles you will have a direct pathway towards ownership from day one. Health and wellbeing Private medical insurance for all UK colleagues. Health cash plan to support you with every day health costs and treatments. Access to Peppy, providing free support from menopause experts for all UK colleagues. A variety of wellbeing support is available through our comprehensive wellbeing program, including access for you and your family. Ability to flex your salary to opt into a wide range of health benefits, many of which can be extended to your family too. Lifestyle A minimum of 33-35 days holiday each year, inclusive of public holidays and dependent on level, with the ability to buy or sell leave through our flexible benefits programme. 10 days additional paid leave for Armed Forces Reservists and Cadet Force Adult Volunteers. Holiday entitlement increased to a minimum of 35 days after 5 years' service. Variety of employee saving schemes and discounts from high street retailers. Enhanced family and carers leave Enhanced family leave policies, including 26 weeks paid maternity and adoption leave, and two weeks paid paternity/partner leave. Our shared parental leave matches maternity leave meaning we pay up to 24 weeks at full pay. Up to five additional days leave are provided for those with significant caring responsibilities, two of which are paid. We offer policies and dedicated support to help military families balance service life with career and wellbeing. Learning and development Primary annual professional institution subscription. A broad range of opportunities to enhance both technical and soft skills through mentoring, formal training, and self development options. Networks, communities, and social outcomes Join a wide range of groups including our Advanced Employee Networks which support our LGBTQ+, gender, race and ethnicity, disability, and parents/carers communities. We are proud signatories of the Armed Forces Covenant and Gold Award holders in the MOD Employer Recognition Scheme, supported by our dedicated internal Armed Forces Network.
26/07/2026
Full time
Birmingham, United Kingdom / Brighton, United Kingdom / Bristol, United Kingdom / Cardiff, United Kingdom / Glasgow, United Kingdom / London, United Kingdom / Manchester, United Kingdom / Newcastle Upon Tyne, United Kingdom Location/s: London, Cardiff, Bristol, Brighton, Birmingham, Manchester, Glasgow, Newcastle Relocation supported:Not supported, but internal applications are welcome Hiring manager contact: Sam Ahdab Mott MacDonald is a global engineering, management, and development consultancy with over 20,000 employees across more than 50 countries and 140+ offices. We work across incredible global industries, delivering exciting work that is defining our future and making an important societal impact in the communities we serve. Our people power our performance - we succeed when they do. With countless opportunities to collaborate, learn, and grow, the possibilities for excellence are as varied as every individual. Whether you want to grow as a subject matter expert or broaden your experience with roles across our international community, you're surrounded by global specialists who want to combine their expertise and champion you to be your best. As a proudly employee owned business, we benefit our clients, our communities, and each other, investing in creating the right space for everyone to feel empowered, included, and valued. Whatever your ambition, Mott MacDonald is where people come to be brilliant. Overview of the role: We are looking for a Principal Data Scientist to help shape the design, development and delivery of production grade AI, machine learning and data science solutions across Mott MacDonald. The role will focus on turning complex business, engineering and environmental needs into scalable, reliable data products and AI services. The successful candidate will bring technical experience across generative AI, large language models, retrieval augmented generation, machine learning, computer vision, geospatial data science and MLOps. They will work with multidisciplinary teams to identify valuable use cases, shape solution architecture, develop reliable models and ensure solutions are tested, monitored and improved in live use. The role includes end to end AI and data science delivery; setting standards for model development, evaluation and deployment; building reusable internal AI services; coaching data scientists and engineers; contributing to AI governance; and translating technical opportunities into clear business value for project teams and senior stakeholders. Candidate Specifications: Experience delivering production data science, machine learning or AI in an enterprise environment. Practical experience in Python and modern machine learning frameworks such as PyTorch, TensorFlow or Keras. Practical experience with generative AI, large language models, embedding models, retrieval augmented generation, AI agents, model evaluation and fine tuning techniques. Experience designing and operating end to end MLOps workflows, including model training, deployment, monitoring, automation and continuous improvement. Ability to work across cloud and engineering environments, including tools such as Azure, Kubernetes, Docker, MLflow, GitHub Actions, Terraform or Databricks. Clear communication and stakeholder engagement skills, with the ability to explain complex technical concepts in accessible business language. Experience coaching, mentoring or giving technical guidance to data scientists, machine learning engineers or data professionals Experience applying computer vision, geospatial data science or predictive modelling to engineering, infrastructure, environmental or asset management work. Knowledge of tools and methods such as LangChain, LLM orchestration, agentic tool use, segmentation foundation models, zero/few shot visual understanding Experience developing reusable internal AI platforms, foundation model services or automation capabilities for use by wider teams. Postgraduate qualification or equivalent research experience in data science, engineering, computer science, applied mathematics or a related discipline. Evidence of innovation, publication, award recognition or contribution to data science practice. UK Immigration Mott MacDonald Ltd. are not currently offering sponsorship to candidates under the Skilled Worker visa route in the UK. This decision is as a consequence of the changes made to the Skilled Worker route by the UK Government in April 2024. We continue to welcome applications from candidates who are eligible for alternative immigration routes in the UK, that do not require sponsorship as a Skilled Worker now or in future. At Mott MacDonald, we believe it makes business sense for you and your manager to choose how you can work most effectively to meet your client, team, and personal commitments. We offer a hybrid working policy that embraces your well being, flexibility, and trust. Equality, diversity, and inclusion We put equality, diversity, and inclusion at the heart of our business, seeking to promote fair employment procedures and practices to ensure equal opportunities for all. We encourage individual expression in our workplace and are committed to creating an inclusive environment where everyone feels they can contribute. Accessibility We want you to perform your best at every stage in the recruitment process. If you are disabled or need any support to enable you to apply or attend an interview, please contact us at and we will talk to you about how we can support you. Financial wellbeing We match employee pension contributions between 4.5% and 7%. Life assurance equal up to 4 x your basic salary, with an option to increase the level of cover to 6 x your salary. Our income protection scheme provides a financial benefit, as well as absence and return to work support due to long term illness or injury. Flexible benefits, including increased life assurance cover, critical illness insurance, payroll saving and will writing. As an independently owned business we share the financial success of the business with all our colleagues in various ways including annual bonus schemes. Employee Ownership Our employee ownership model means no external investors, just us, creating a culture of shared success. Our employees have a stake and a voice in our business, giving them a direct connection to our success through our personal and group performance bonuses. As your career grows, so does your stake, recognising your long term impact and contribution. Your voice matters, with the opportunity to connect directly with senior leadership through formal channels to help shape our future. For our senior roles you will have a direct pathway towards ownership from day one. Health and wellbeing Private medical insurance for all UK colleagues. Health cash plan to support you with every day health costs and treatments. Access to Peppy, providing free support from menopause experts for all UK colleagues. A variety of wellbeing support is available through our comprehensive wellbeing program, including access for you and your family. Ability to flex your salary to opt into a wide range of health benefits, many of which can be extended to your family too. Lifestyle A minimum of 33-35 days holiday each year, inclusive of public holidays and dependent on level, with the ability to buy or sell leave through our flexible benefits programme. 10 days additional paid leave for Armed Forces Reservists and Cadet Force Adult Volunteers. Holiday entitlement increased to a minimum of 35 days after 5 years' service. Variety of employee saving schemes and discounts from high street retailers. Enhanced family and carers leave Enhanced family leave policies, including 26 weeks paid maternity and adoption leave, and two weeks paid paternity/partner leave. Our shared parental leave matches maternity leave meaning we pay up to 24 weeks at full pay. Up to five additional days leave are provided for those with significant caring responsibilities, two of which are paid. We offer policies and dedicated support to help military families balance service life with career and wellbeing. Learning and development Primary annual professional institution subscription. A broad range of opportunities to enhance both technical and soft skills through mentoring, formal training, and self development options. Networks, communities, and social outcomes Join a wide range of groups including our Advanced Employee Networks which support our LGBTQ+, gender, race and ethnicity, disability, and parents/carers communities. We are proud signatories of the Armed Forces Covenant and Gold Award holders in the MOD Employer Recognition Scheme, supported by our dedicated internal Armed Forces Network.
We are looking for a Senior AI Engineer to join our growing Applied AI team. This is ahands-on, technically demanding role for someone who can contribute to building production AI systems while helping raise the technical bar of the team around them. You will work collaboratively across a fast-moving technology company, turningcutting-edgeresearch into practical, scalable solutions.This role reportsto the AppliedAILead. Responsibilities Lead data identification, cleaning, enrichment, preprocessing,feature engineering,andexploratoryanalysis to ensure fitness for AI workflows and to inform modelling and business decisions. Build, tune, andoptimisemachine learning, deep learning, and generative AI models,leveragingboth established andcutting-edgetechniques. Designand buildLLM-powered systems- RAG pipelines, prompt and context engineering, fine-tuning, structured outputs, function calling, context-window management,and secure model integration;selectingappropriately between standard and reasoning (test-time-compute) models, balancing capability against latency and cost. Designand buildagentic AI systems- tool-calling architectures, interoperability protocols (MCP, agent-to-agent), multi-agent orchestration, and multi-step reasoning with human-in-the-loop andappropriate trust, safety, and security boundaries. Leverageand contributeto agentic engineering tooling, including coding assistants,configurable permissions models,internal skills and plugins architectures, and sandboxed autonomous workflows integrated intoCI/CDand delivery pipelines. Applymodel adaptation techniques including parameter-efficient fine-tuning(LoRA,QLoRA), modeldistillation, and synthetic data generation for domain-specific and low-resource scenarios. Develop evaluation frameworks covering performance, hallucination, safety, cost, and non-deterministicbehaviouracross classical and generative AI systems. Optimisemodel inference and end-to-end pipelines for speed, cost, memory footprint, and scalability, including for CPU-constrained andairgappeddeployment targets. Develop andmaintainproduction-grade model pipelines and supporting software with strongMLOpspractices - covering real-time inference, batch processing, performance monitoring, drift detection, scheduled retraining, observability, governance, version control, and reproducibility. Providetechnicalguidance- architectural input, peer review, and mentoring of mid-level and junior engineers through code review, pairing, and knowledge sharing - raising the technical bar of the team and shaping secure, scalable, high-performing AI solutions. Work within Agile delivery teams - collaborating with data, platform, and software engineers to integrate AI into products, communicating clearly with technical and non-technical stakeholders, and championing engineering excellence and continuous improvement. Stay current with the latest research, frameworks, and trends across ML, deep learning, and GenAI, translating them into production-ready solutions. Required Knowledge, experience and values 5+ years of commercialexperience in AI and machine learning engineering and development - academic research experience is highly valued alongside this, buta track recordof commercial delivery is essential -withdemonstrabledelivery of production-grade models and systems across traditional ML, neural networks, and LLM-based systems. 5+years of commercial experience working withPython;familiaritywith C# is considered a bonus due to existing product integrations. Hold an advanced degree in machine learning, computer science, engineering, or a related discipline, with an MScrequiredand a PhD highly desirable. Deep hands-on experience withPyTorch, Scikit-learn, and the Hugging Face ecosystem, with familiarity withMLFlowandAzureML; capable of making architecture and implementation decisions. Strong competence with Git, pull requests, automated testing, CI/CD,MLOps, and ML pipelines; experience with Azure DevOps and cloud-based ML infrastructure (Azure, AWS, or GCP) is beneficial. Strong grounding inclassical data science fundamentals - feature engineering, statistical analysis, experimental design, and model monitoring - alongside benchmarkingand the evaluation of non-deterministic AI systems. Practical experience with inferenceoptimisationincludingquantisation, latency reduction, cost-aware model selection, and resource-efficient deployment. Communicate clearly, translating complex technical work into actionable recommendations, and produce high-quality documentation including technical decision records. Operate independently and make sound technical decisions within complex, ambiguous contexts, witha track recordof owning problems end-to-end. Prior cybersecurity or business domainexpertiseis not a prerequisite, although would be highly relevant. We encourage you to apply even if your experience is not a 100% match with the position. Beneficial Knowledge, experience, and values Familiarity with containerisation (Docker, Kubernetes), event-driven or microservices architectures, and distributed data processing at scale. Experience with embedding pipelines, vector search, and semantic retrieval for RAG systems. Knowledge of LLM evaluation techniques including structured evals frameworks, hallucination mitigation, benchmarking, and human-in-the-loop evaluation. Understanding of AI safety, responsible AI principles, governance, and regulatoryand standardsawareness (e.g. EU AI Act, NIST AI RMF, ISO/IEC 42001), including bias detection, explainability, and auditability. Familiarity with security best practices in AI systems, particularly around prompt injection risks, data handling, and model misuse. Understanding of AI applied in cybersecurity contexts, including concept drift, adversarial robustness, andmodel assurance challenges. Exposure to data engineering practices including ETL/ELT pipelines, data versioning, and schema management. Awareness of multi-modal data handling include vision, audio, or document-based inputs. Contributions to open-source projects, research publications, or participation in AI/ML communities and conferences. Demonstrated curiosity and ability to balance research-oriented thinking with pragmatic engineering delivery in a commercial environment. About Us We didn't start out as a traditional security product. In the beginning, Glasswall was one of only two file sanitization filters in the US Intelligence Community's highly classified networks. We are rated by the National Security Agency. We designed Glasswall CDR to protect businesses against the most advanced file-based threats. Today, we're trusted by commercial and government organisations around the world. In June 2025 Glasswall officially entered a new era of growth and innovation having been acquired by the leading private equity firm, PSG Equity. This marks a significant milestone for our company and one that underscores the strength of our business, the dedication of our team, and the exciting potential that lies ahead. With PSG's strong track record of scaling high-growth cybersecurity and technology businesses, we are better positioned than ever to accelerate innovation, expand into new markets, and deliver even greater value to our clients, employees, and stakeholders. Cybersecurity is a mission-critical field, and we've always believed that staying ahead means moving faster, continually adapting to meet new challenges and investing more boldly in the future. This partnership empowers us to do exactly that while maintaining the same leadership, values, and commitment to excellence that have brought us this far We're excited for what's to come so now is a great time for you to join us on our journey. Inclusion At Glasswall we believe that diversity of people and thought are central to our purpose. We are committed to making Glasswall a company that is attractive to people of many different backgrounds. This includes diversity in every sense of the word: those with different backgrounds, ages, ethnicities, gender identities, sexual orientations, ways of thinking and those with disabilities or neurodivergent conditions. We therefore welcome and encourage applications from everyone, including those from groups that are under-represented in our workforce. One of our corporate objectives is to ensure that the organisational health of the firm is highly rated by our employees. We believe that this is only possible if we promote a culture of inclusion and respect across our business. Every six months we survey employees on a range of questions relating to our organisational health. This holds a mirror-up to a business and ensures that we can focus on where we need to do better. We have an Organisational Health Committee, which is chaired by a non-executive position. The panel has been formed to guide the leadership in taking positive action that supports a good work-life balance, family friendly relations and to be inviting to a diverse range of potential employees. We also have a Women in Technology Group which has been formed to promote balance in the way that we communicate with, promote, encourage, and support people across our business. Work/Life Balance Our team puts a high value on work-life balance. It isn't about how many hours you spend at home or at work; it's about the flow you establish that brings energy to both parts of your life . click apply for full job details
26/07/2026
Full time
We are looking for a Senior AI Engineer to join our growing Applied AI team. This is ahands-on, technically demanding role for someone who can contribute to building production AI systems while helping raise the technical bar of the team around them. You will work collaboratively across a fast-moving technology company, turningcutting-edgeresearch into practical, scalable solutions.This role reportsto the AppliedAILead. Responsibilities Lead data identification, cleaning, enrichment, preprocessing,feature engineering,andexploratoryanalysis to ensure fitness for AI workflows and to inform modelling and business decisions. Build, tune, andoptimisemachine learning, deep learning, and generative AI models,leveragingboth established andcutting-edgetechniques. Designand buildLLM-powered systems- RAG pipelines, prompt and context engineering, fine-tuning, structured outputs, function calling, context-window management,and secure model integration;selectingappropriately between standard and reasoning (test-time-compute) models, balancing capability against latency and cost. Designand buildagentic AI systems- tool-calling architectures, interoperability protocols (MCP, agent-to-agent), multi-agent orchestration, and multi-step reasoning with human-in-the-loop andappropriate trust, safety, and security boundaries. Leverageand contributeto agentic engineering tooling, including coding assistants,configurable permissions models,internal skills and plugins architectures, and sandboxed autonomous workflows integrated intoCI/CDand delivery pipelines. Applymodel adaptation techniques including parameter-efficient fine-tuning(LoRA,QLoRA), modeldistillation, and synthetic data generation for domain-specific and low-resource scenarios. Develop evaluation frameworks covering performance, hallucination, safety, cost, and non-deterministicbehaviouracross classical and generative AI systems. Optimisemodel inference and end-to-end pipelines for speed, cost, memory footprint, and scalability, including for CPU-constrained andairgappeddeployment targets. Develop andmaintainproduction-grade model pipelines and supporting software with strongMLOpspractices - covering real-time inference, batch processing, performance monitoring, drift detection, scheduled retraining, observability, governance, version control, and reproducibility. Providetechnicalguidance- architectural input, peer review, and mentoring of mid-level and junior engineers through code review, pairing, and knowledge sharing - raising the technical bar of the team and shaping secure, scalable, high-performing AI solutions. Work within Agile delivery teams - collaborating with data, platform, and software engineers to integrate AI into products, communicating clearly with technical and non-technical stakeholders, and championing engineering excellence and continuous improvement. Stay current with the latest research, frameworks, and trends across ML, deep learning, and GenAI, translating them into production-ready solutions. Required Knowledge, experience and values 5+ years of commercialexperience in AI and machine learning engineering and development - academic research experience is highly valued alongside this, buta track recordof commercial delivery is essential -withdemonstrabledelivery of production-grade models and systems across traditional ML, neural networks, and LLM-based systems. 5+years of commercial experience working withPython;familiaritywith C# is considered a bonus due to existing product integrations. Hold an advanced degree in machine learning, computer science, engineering, or a related discipline, with an MScrequiredand a PhD highly desirable. Deep hands-on experience withPyTorch, Scikit-learn, and the Hugging Face ecosystem, with familiarity withMLFlowandAzureML; capable of making architecture and implementation decisions. Strong competence with Git, pull requests, automated testing, CI/CD,MLOps, and ML pipelines; experience with Azure DevOps and cloud-based ML infrastructure (Azure, AWS, or GCP) is beneficial. Strong grounding inclassical data science fundamentals - feature engineering, statistical analysis, experimental design, and model monitoring - alongside benchmarkingand the evaluation of non-deterministic AI systems. Practical experience with inferenceoptimisationincludingquantisation, latency reduction, cost-aware model selection, and resource-efficient deployment. Communicate clearly, translating complex technical work into actionable recommendations, and produce high-quality documentation including technical decision records. Operate independently and make sound technical decisions within complex, ambiguous contexts, witha track recordof owning problems end-to-end. Prior cybersecurity or business domainexpertiseis not a prerequisite, although would be highly relevant. We encourage you to apply even if your experience is not a 100% match with the position. Beneficial Knowledge, experience, and values Familiarity with containerisation (Docker, Kubernetes), event-driven or microservices architectures, and distributed data processing at scale. Experience with embedding pipelines, vector search, and semantic retrieval for RAG systems. Knowledge of LLM evaluation techniques including structured evals frameworks, hallucination mitigation, benchmarking, and human-in-the-loop evaluation. Understanding of AI safety, responsible AI principles, governance, and regulatoryand standardsawareness (e.g. EU AI Act, NIST AI RMF, ISO/IEC 42001), including bias detection, explainability, and auditability. Familiarity with security best practices in AI systems, particularly around prompt injection risks, data handling, and model misuse. Understanding of AI applied in cybersecurity contexts, including concept drift, adversarial robustness, andmodel assurance challenges. Exposure to data engineering practices including ETL/ELT pipelines, data versioning, and schema management. Awareness of multi-modal data handling include vision, audio, or document-based inputs. Contributions to open-source projects, research publications, or participation in AI/ML communities and conferences. Demonstrated curiosity and ability to balance research-oriented thinking with pragmatic engineering delivery in a commercial environment. About Us We didn't start out as a traditional security product. In the beginning, Glasswall was one of only two file sanitization filters in the US Intelligence Community's highly classified networks. We are rated by the National Security Agency. We designed Glasswall CDR to protect businesses against the most advanced file-based threats. Today, we're trusted by commercial and government organisations around the world. In June 2025 Glasswall officially entered a new era of growth and innovation having been acquired by the leading private equity firm, PSG Equity. This marks a significant milestone for our company and one that underscores the strength of our business, the dedication of our team, and the exciting potential that lies ahead. With PSG's strong track record of scaling high-growth cybersecurity and technology businesses, we are better positioned than ever to accelerate innovation, expand into new markets, and deliver even greater value to our clients, employees, and stakeholders. Cybersecurity is a mission-critical field, and we've always believed that staying ahead means moving faster, continually adapting to meet new challenges and investing more boldly in the future. This partnership empowers us to do exactly that while maintaining the same leadership, values, and commitment to excellence that have brought us this far We're excited for what's to come so now is a great time for you to join us on our journey. Inclusion At Glasswall we believe that diversity of people and thought are central to our purpose. We are committed to making Glasswall a company that is attractive to people of many different backgrounds. This includes diversity in every sense of the word: those with different backgrounds, ages, ethnicities, gender identities, sexual orientations, ways of thinking and those with disabilities or neurodivergent conditions. We therefore welcome and encourage applications from everyone, including those from groups that are under-represented in our workforce. One of our corporate objectives is to ensure that the organisational health of the firm is highly rated by our employees. We believe that this is only possible if we promote a culture of inclusion and respect across our business. Every six months we survey employees on a range of questions relating to our organisational health. This holds a mirror-up to a business and ensures that we can focus on where we need to do better. We have an Organisational Health Committee, which is chaired by a non-executive position. The panel has been formed to guide the leadership in taking positive action that supports a good work-life balance, family friendly relations and to be inviting to a diverse range of potential employees. We also have a Women in Technology Group which has been formed to promote balance in the way that we communicate with, promote, encourage, and support people across our business. Work/Life Balance Our team puts a high value on work-life balance. It isn't about how many hours you spend at home or at work; it's about the flow you establish that brings energy to both parts of your life . click apply for full job details
Build what's next in applied AI at JPMorganChase - where your work shapes how teams use intelligent systems at scale. You'll lead hands-on engineering for agentic and GenAI capabilities that power the LLM Suite platform. This role offers a mix of deep technical problem-solving, architecture ownership, and collaboration with talented builders. If you enjoy turning ambiguity into reliable production systems, you'll thrive here. Join a team that values craft, security, and learning. As an Applied AI ML Lead in LLM Suite Engineering, you will design and deliver production-grade AI/ML and agentic solutions that integrate seamlessly with existing systems. You will own technical direction across architecture, implementation, and operational stability, with a strong focus on secure, high-quality software. You will partner with peers across engineering to identify patterns and improve standards, reliability, and scalability. You will help evolve the platform using modern public cloud services and agentic frameworks. You will contribute to a collaborative culture through communities of practice and emerging-technology events. You will explore and operationalize emerging patterns such as agent-to-agent communication, model context protocols, and agentic orchestration, turning early-stage concepts into scalable, production-ready capabilities. Job Responsibilities Design, develop, and troubleshoot software solutions using creative approaches to solve complex technical challenges Write secure, high-quality production code and maintain algorithms that integrate with existing systems Create architecture and design artifacts for complex applications, ensuring design constraints are met through delivery Build AI/ML solutions and agentic systems for the LLM Suite platform using public cloud architecture (Azure, AWS) and modern agentic frameworks Implement GenAI services leveraging Azure OpenAI models and AWS Bedrock Identify hidden problems and patterns in data proactively to improve coding standards and system architecture Participate in software engineering communities of practice and events focused on emerging technologies Required Qualifications, Capabilities, and Skills Computer science degree or equivalent practical experience Hands-on experience with system design, application development, testing, and operational stability Proficiency in Python (FastAPI) Experience building microservices and APIs Experience with elastic compute, NoSQL databases, and messaging queues Strong understanding of the Software Development Life Cycle Solid grasp of CI/CD, application resiliency, and security Preferred Qualifications, Capabilities, and Skills Experience implementing GenAI services leveraging Azure OpenAI models and AWS Bedrock Proficiency working with large language models and building agents with LangGraph Experience developing, debugging, and maintaining code in a large corporate environment using modern programming and database querying languages Experience with containerization Knowledge of agent-to-agent (A2A) communication concepts Familiarity with Model Context Protocol (MCP) Experience with agentic orchestrators, personal AI assistants, or AI skills development J.P. Morgan is a global leader in financial services, providing strategic advice and products to the world's most prominent corporations, governments, wealthy individuals and institutional investors. Our first-class business in a first-class way approach to serving clients drives everything we do. We strive to build trusted, long-term partnerships to help our clients achieve their business objectives. We recognize that our people are our strength and the diverse talents they bring to our global workforce are directly linked to our success. We are an equal opportunity employer and place a high value on diversity and inclusion at our company. We do not discriminate on the basis of any protected attribute, including race, religion, color, national origin, gender, sexual orientation, gender identity, gender expression, age, marital or veteran status, pregnancy or disability, or any other basis protected under applicable law. We also make reasonable accommodations for applicants' and employees' religious practices and beliefs, as well as mental health or physical disability needs. Visit our FAQs for more information about requesting an accommodation. Our Corporate Technology team relies on smart, driven people like you to develop applications and provide tech support for all our corporate functions across our network. Your efforts will touch lives all over the financial spectrum and across all our divisions: Global Finance, Corporate Treasury, Risk Management, Human Resources, Compliance, Legal, and within the Corporate Administrative Office. You'll be part of a team specifically built to meet and exceed our evolving technology needs, as well as our technology controls agenda. Lead applied AI and engineering to build secure, scalable agentic solutions within our LLM suite.
26/07/2026
Full time
Build what's next in applied AI at JPMorganChase - where your work shapes how teams use intelligent systems at scale. You'll lead hands-on engineering for agentic and GenAI capabilities that power the LLM Suite platform. This role offers a mix of deep technical problem-solving, architecture ownership, and collaboration with talented builders. If you enjoy turning ambiguity into reliable production systems, you'll thrive here. Join a team that values craft, security, and learning. As an Applied AI ML Lead in LLM Suite Engineering, you will design and deliver production-grade AI/ML and agentic solutions that integrate seamlessly with existing systems. You will own technical direction across architecture, implementation, and operational stability, with a strong focus on secure, high-quality software. You will partner with peers across engineering to identify patterns and improve standards, reliability, and scalability. You will help evolve the platform using modern public cloud services and agentic frameworks. You will contribute to a collaborative culture through communities of practice and emerging-technology events. You will explore and operationalize emerging patterns such as agent-to-agent communication, model context protocols, and agentic orchestration, turning early-stage concepts into scalable, production-ready capabilities. Job Responsibilities Design, develop, and troubleshoot software solutions using creative approaches to solve complex technical challenges Write secure, high-quality production code and maintain algorithms that integrate with existing systems Create architecture and design artifacts for complex applications, ensuring design constraints are met through delivery Build AI/ML solutions and agentic systems for the LLM Suite platform using public cloud architecture (Azure, AWS) and modern agentic frameworks Implement GenAI services leveraging Azure OpenAI models and AWS Bedrock Identify hidden problems and patterns in data proactively to improve coding standards and system architecture Participate in software engineering communities of practice and events focused on emerging technologies Required Qualifications, Capabilities, and Skills Computer science degree or equivalent practical experience Hands-on experience with system design, application development, testing, and operational stability Proficiency in Python (FastAPI) Experience building microservices and APIs Experience with elastic compute, NoSQL databases, and messaging queues Strong understanding of the Software Development Life Cycle Solid grasp of CI/CD, application resiliency, and security Preferred Qualifications, Capabilities, and Skills Experience implementing GenAI services leveraging Azure OpenAI models and AWS Bedrock Proficiency working with large language models and building agents with LangGraph Experience developing, debugging, and maintaining code in a large corporate environment using modern programming and database querying languages Experience with containerization Knowledge of agent-to-agent (A2A) communication concepts Familiarity with Model Context Protocol (MCP) Experience with agentic orchestrators, personal AI assistants, or AI skills development J.P. Morgan is a global leader in financial services, providing strategic advice and products to the world's most prominent corporations, governments, wealthy individuals and institutional investors. Our first-class business in a first-class way approach to serving clients drives everything we do. We strive to build trusted, long-term partnerships to help our clients achieve their business objectives. We recognize that our people are our strength and the diverse talents they bring to our global workforce are directly linked to our success. We are an equal opportunity employer and place a high value on diversity and inclusion at our company. We do not discriminate on the basis of any protected attribute, including race, religion, color, national origin, gender, sexual orientation, gender identity, gender expression, age, marital or veteran status, pregnancy or disability, or any other basis protected under applicable law. We also make reasonable accommodations for applicants' and employees' religious practices and beliefs, as well as mental health or physical disability needs. Visit our FAQs for more information about requesting an accommodation. Our Corporate Technology team relies on smart, driven people like you to develop applications and provide tech support for all our corporate functions across our network. Your efforts will touch lives all over the financial spectrum and across all our divisions: Global Finance, Corporate Treasury, Risk Management, Human Resources, Compliance, Legal, and within the Corporate Administrative Office. You'll be part of a team specifically built to meet and exceed our evolving technology needs, as well as our technology controls agenda. Lead applied AI and engineering to build secure, scalable agentic solutions within our LLM suite.
Join Pigment: The AI Platform Redefining Business Planning Pigment is the AI-powered business planning and performance management platform built for agility and scale. We connect people, data, and processes in one intuitive, feature-rich solution, empowering every team-from Finance to HR-to build, adapt, and align strategic plans in real time. Founded in 2019, Pigment is one of the fastest-growing SaaS companies globally. Industry leaders like Unilever, Snowflake, Siemens, and DPD use Pigment daily to make more informed decisions and confidently navigate any scenario. With a team of 600+ across Paris, London, New York, Toronto, San Francisco and Austin, we've raised nearly $400M from top-tier investors and were named a Visionary in the 2024 Gartner Magic Quadrant for Financial Planning Software. At Pigment, we take smart risks, celebrate bold ideas, and challenge the status quo-all while working as one team. If you're driven by innovation and ready to make an impact at scale, we'd love to hear from you. What you'll do We are looking for an AI Deployment Strategist to join our growing team. In this role, you will work directly with customers to design, build, and deploy AI-powered planning solutions using Pigment. This is a highly cross-functional role at the intersection of engineering, data, and business problem-solving. You will own the end-to-end implementation of Pigment's AI capabilities for strategic customers - from translating business problems into models, to deploying agentic AI solutions in production. You will play a key role in shaping how organizations leverage Pigment to transform their planning processes, while acting as a critical feedback loop between customers and our Product and Engineering teams. What you'll work on Build & deploy AI-powered solutions Translate complex business problems into scalable Pigment models using AI agents, formulas, dimensions, and advanced logic Design, build, and deploy custom AI agents tailored to customer workflows and decision-making processes Own end-to-end implementation of Pigment for key customers Work directly with customers Partner with business and technical stakeholders to rethink processes and design AI-driven solutions Act as a trusted advisor, guiding customers on best practices Drive adoption and ensure customers maximize value from Pigment Prototype & innovate Develop prototypes and experimental AI use cases to solve emerging customer needs Test and iterate on new approaches to agent-based planning and automation Bridge product, engineering, and customers Collaborate closely with Customer Success, Solutions Architects, and Product teams Translate customer feedback into clear product requirements and specifications Contribute to the evolution of Pigment's AI capabilities Enable and scale Train users and teams on Pigment features, modeling best practices, and scalable system design Help define repeatable patterns and frameworks for AI deployments across customers What we're looking for Required Engineering or computer science degree from top tier institution 2-5 years in a technical, client-facing, or implementation role, such as: Forward Deployed Engineer Data Scientist / AI Engineer Solutions Architect / Solutions Engineer Technical or Implementation Consultant Strong analytical and problem-solving skills with experience in: Data modeling, analytics, or business logic design AI / ML concepts or applied data workflows Proficiency with: Formulas, logic, and structured modeling Programming (Python, SQL, or similar is a plus) Familiarity with: SaaS platforms or planning tools APIs, data pipelines, and system integration concepts Ability to manage multiple stakeholders and projects in fast-paced environments Nice to have Background in FP&A, financial modeling, or business planning workflows Prior experience with Pigment or similar platforms Additional European language(s) outside of English What success looks like Customers successfully deploy and adopt AI-powered planning workflows Innovative agentic AI solutions are built and scaled across use cases You are seen as a trusted technical partner by customers Strong feedback loops drive continuous product improvement Repeatable patterns emerge to scale AI deployments across Pigment customers We conduct background checks as part of our hiring process, in accordance with applicable laws and regulations in the countries where we operate. This may include verification of employment history, education, and, where legally permitted, criminal records. Any checks will be conducted lawfully prior to formal employment contracts being signed, with candidate consent, and information will be treated confidentially. Pigment is an equal opportunity employer. We believe diversity is a strength and fosters innovation. We are committed to enabling everyone to feel included and valued at the workplace. All qualified applicants will receive consideration for employment without regard to age, color, family, gender identity, marital status, national origin, physical or mental disability, sex (including pregnancy), sexual orientation, social origin, or any other characteristic protected by applicable laws. We may process your personal data in accordance with our HR Data Protection Notice.
26/07/2026
Full time
Join Pigment: The AI Platform Redefining Business Planning Pigment is the AI-powered business planning and performance management platform built for agility and scale. We connect people, data, and processes in one intuitive, feature-rich solution, empowering every team-from Finance to HR-to build, adapt, and align strategic plans in real time. Founded in 2019, Pigment is one of the fastest-growing SaaS companies globally. Industry leaders like Unilever, Snowflake, Siemens, and DPD use Pigment daily to make more informed decisions and confidently navigate any scenario. With a team of 600+ across Paris, London, New York, Toronto, San Francisco and Austin, we've raised nearly $400M from top-tier investors and were named a Visionary in the 2024 Gartner Magic Quadrant for Financial Planning Software. At Pigment, we take smart risks, celebrate bold ideas, and challenge the status quo-all while working as one team. If you're driven by innovation and ready to make an impact at scale, we'd love to hear from you. What you'll do We are looking for an AI Deployment Strategist to join our growing team. In this role, you will work directly with customers to design, build, and deploy AI-powered planning solutions using Pigment. This is a highly cross-functional role at the intersection of engineering, data, and business problem-solving. You will own the end-to-end implementation of Pigment's AI capabilities for strategic customers - from translating business problems into models, to deploying agentic AI solutions in production. You will play a key role in shaping how organizations leverage Pigment to transform their planning processes, while acting as a critical feedback loop between customers and our Product and Engineering teams. What you'll work on Build & deploy AI-powered solutions Translate complex business problems into scalable Pigment models using AI agents, formulas, dimensions, and advanced logic Design, build, and deploy custom AI agents tailored to customer workflows and decision-making processes Own end-to-end implementation of Pigment for key customers Work directly with customers Partner with business and technical stakeholders to rethink processes and design AI-driven solutions Act as a trusted advisor, guiding customers on best practices Drive adoption and ensure customers maximize value from Pigment Prototype & innovate Develop prototypes and experimental AI use cases to solve emerging customer needs Test and iterate on new approaches to agent-based planning and automation Bridge product, engineering, and customers Collaborate closely with Customer Success, Solutions Architects, and Product teams Translate customer feedback into clear product requirements and specifications Contribute to the evolution of Pigment's AI capabilities Enable and scale Train users and teams on Pigment features, modeling best practices, and scalable system design Help define repeatable patterns and frameworks for AI deployments across customers What we're looking for Required Engineering or computer science degree from top tier institution 2-5 years in a technical, client-facing, or implementation role, such as: Forward Deployed Engineer Data Scientist / AI Engineer Solutions Architect / Solutions Engineer Technical or Implementation Consultant Strong analytical and problem-solving skills with experience in: Data modeling, analytics, or business logic design AI / ML concepts or applied data workflows Proficiency with: Formulas, logic, and structured modeling Programming (Python, SQL, or similar is a plus) Familiarity with: SaaS platforms or planning tools APIs, data pipelines, and system integration concepts Ability to manage multiple stakeholders and projects in fast-paced environments Nice to have Background in FP&A, financial modeling, or business planning workflows Prior experience with Pigment or similar platforms Additional European language(s) outside of English What success looks like Customers successfully deploy and adopt AI-powered planning workflows Innovative agentic AI solutions are built and scaled across use cases You are seen as a trusted technical partner by customers Strong feedback loops drive continuous product improvement Repeatable patterns emerge to scale AI deployments across Pigment customers We conduct background checks as part of our hiring process, in accordance with applicable laws and regulations in the countries where we operate. This may include verification of employment history, education, and, where legally permitted, criminal records. Any checks will be conducted lawfully prior to formal employment contracts being signed, with candidate consent, and information will be treated confidentially. Pigment is an equal opportunity employer. We believe diversity is a strength and fosters innovation. We are committed to enabling everyone to feel included and valued at the workplace. All qualified applicants will receive consideration for employment without regard to age, color, family, gender identity, marital status, national origin, physical or mental disability, sex (including pregnancy), sexual orientation, social origin, or any other characteristic protected by applicable laws. We may process your personal data in accordance with our HR Data Protection Notice.
Fairygodboss is seeking an Applied AI/ML Lead Engineer to design and build Generative AI solutions. You will work on automation and user experience improvements using advanced AI tools. The ideal candidate will have a strong background in AI/ML delivery and backend engineering, proficiency in Java and Python, and experience deploying solutions on cloud-native platforms. This is an opportunity to significantly impact business workflows through innovative AI applications.
26/07/2026
Full time
Fairygodboss is seeking an Applied AI/ML Lead Engineer to design and build Generative AI solutions. You will work on automation and user experience improvements using advanced AI tools. The ideal candidate will have a strong background in AI/ML delivery and backend engineering, proficiency in Java and Python, and experience deploying solutions on cloud-native platforms. This is an opportunity to significantly impact business workflows through innovative AI applications.
As a Applied AI/ML Lead Engineer in our Applied AI ML - Python & Agentic AI team, you will design, build, and productionize Generative AI and Agentic AI solutions. The ideal candidate brings a balanced mix of modern AI/ML delivery (LLMs/SLMs, RAG, tool using agents, evaluation, MLOps) and backend/service engineering (Java and/or Python, APIs/microservices, testing, CI/CD, observability, reliability) on AWS and cloud native platforms. This role values modern AI engineering workflows and tooling such as GitHub Copilot and Claude Code to accelerate delivery while maintaining quality and security. Familiarity with MCP (Model Context Protocol), Agent Skills and designing agentic systems that integrate models with tools and enterprise data via structured interfaces is a plus. Job Responsibilities Design, develop, and deploy GenAI and Agentic AI solutions that improve automation, decision making, and user experience across business workflows. Build LLM/SLM powered applications including RAG based systems, summarization/extraction pipelines, chat/coplay experiences, and tool using agents. Engineer production grade services using Java and/or Python (REST/gRPC APIs, microservices, libraries), following secure coding and reliability best practices. Develop prompt strategies and prompt engineering assets (templates, routing, guardrails), and implement automated evaluation to improve quality over time. Build and maintain data pipelines and processing workflows required for ML/GenAI use cases using cloud services. Apply MLOps practices across the lifecycle: experimentation, versioning, CI/CD, deployment, monitoring, and maintenance for models/prompts/agents. Implement robust testing (unit/integration), performance benchmarking (latency/cost), and observability (logging/metrics/tracing) for AI services. Collaborate with cross functional stakeholders to define requirements, success metrics, and rollout plans; communicate complex topics clearly to technical and non technical audiences. Strong problem solving skills and ability to work effectively in ambiguous environments with multiple stakeholders. Required Qualifications, Capabilities, and Skills Undergrad or Master's degree (or equivalent practical experience) in Computer Science, Data Science, Machine Learning, or related field. Hands on experience building applied AI/ML or GenAI solutions (e.g., RAG, classification, extraction, ranking, summarization, copilots). Familiarity with MCP (Model Context Protocol), Agent Skills and architectures that connect models to tools/data through standardized interfaces. Familiarity with LLM application patterns: embeddings/vector search, prompt orchestration, tool calling/function calling, safety/guardrails, evaluation. Strong software engineering experience delivering production systems; ability to design maintainable architectures and write clean, testable code. Proficiency in Java and/or Python and experience building APIs/services and integrating with data sources and downstream systems. Experience deploying solutions on AWS and cloud native environments; understanding of security fundamentals and operational excellence. Experience with modern engineering practices: CI/CD, code reviews, unit testing (e.g., pytest/JUnit), and deployment automation. Experience with containers and orchestration (e.g., Docker, Kubernetes/EKS) and production monitoring practices. Preferred Qualifications, Capabilities, and Skills Experience building agentic AI systems (multi step workflows, tool routing, planning, memory patterns, supervision/fallback strategies). Experience with AWS Bedrock and/or SageMaker (or equivalent managed ML/GenAI platforms) and deployment patterns for scalable inference. Experience with evaluation frameworks and approaches (golden datasets, LLM as judge, human in the loop review, red teaming). Experience fine tuning models (e.g., LoRA/QLoRA/DoRA) and/or working with SLMs, embeddings, and retrieval systems. Experience with developer productivity tooling such as GitHub Copilot and Claude Code, paired with strong SDLC controls. Knowledge of the financial services industry and operating in regulated environments (auditability, controls, data handling). Exposure to distributed compute/training concepts (e.g., DDP, sharding) and performance/cost optimization. We are an equal opportunity employer and place a high value on diversity and inclusion at our company. We do not discriminate on the basis of any protected attribute, including race, religion, color, national origin, gender, sexual orientation, gender identity, pregnancy or disability, or any other basis protected under applicable law. We also make reasonable accommodations for applicants and employees' religious practices and beliefs, as well as mental health or physical disability needs.
26/07/2026
Full time
As a Applied AI/ML Lead Engineer in our Applied AI ML - Python & Agentic AI team, you will design, build, and productionize Generative AI and Agentic AI solutions. The ideal candidate brings a balanced mix of modern AI/ML delivery (LLMs/SLMs, RAG, tool using agents, evaluation, MLOps) and backend/service engineering (Java and/or Python, APIs/microservices, testing, CI/CD, observability, reliability) on AWS and cloud native platforms. This role values modern AI engineering workflows and tooling such as GitHub Copilot and Claude Code to accelerate delivery while maintaining quality and security. Familiarity with MCP (Model Context Protocol), Agent Skills and designing agentic systems that integrate models with tools and enterprise data via structured interfaces is a plus. Job Responsibilities Design, develop, and deploy GenAI and Agentic AI solutions that improve automation, decision making, and user experience across business workflows. Build LLM/SLM powered applications including RAG based systems, summarization/extraction pipelines, chat/coplay experiences, and tool using agents. Engineer production grade services using Java and/or Python (REST/gRPC APIs, microservices, libraries), following secure coding and reliability best practices. Develop prompt strategies and prompt engineering assets (templates, routing, guardrails), and implement automated evaluation to improve quality over time. Build and maintain data pipelines and processing workflows required for ML/GenAI use cases using cloud services. Apply MLOps practices across the lifecycle: experimentation, versioning, CI/CD, deployment, monitoring, and maintenance for models/prompts/agents. Implement robust testing (unit/integration), performance benchmarking (latency/cost), and observability (logging/metrics/tracing) for AI services. Collaborate with cross functional stakeholders to define requirements, success metrics, and rollout plans; communicate complex topics clearly to technical and non technical audiences. Strong problem solving skills and ability to work effectively in ambiguous environments with multiple stakeholders. Required Qualifications, Capabilities, and Skills Undergrad or Master's degree (or equivalent practical experience) in Computer Science, Data Science, Machine Learning, or related field. Hands on experience building applied AI/ML or GenAI solutions (e.g., RAG, classification, extraction, ranking, summarization, copilots). Familiarity with MCP (Model Context Protocol), Agent Skills and architectures that connect models to tools/data through standardized interfaces. Familiarity with LLM application patterns: embeddings/vector search, prompt orchestration, tool calling/function calling, safety/guardrails, evaluation. Strong software engineering experience delivering production systems; ability to design maintainable architectures and write clean, testable code. Proficiency in Java and/or Python and experience building APIs/services and integrating with data sources and downstream systems. Experience deploying solutions on AWS and cloud native environments; understanding of security fundamentals and operational excellence. Experience with modern engineering practices: CI/CD, code reviews, unit testing (e.g., pytest/JUnit), and deployment automation. Experience with containers and orchestration (e.g., Docker, Kubernetes/EKS) and production monitoring practices. Preferred Qualifications, Capabilities, and Skills Experience building agentic AI systems (multi step workflows, tool routing, planning, memory patterns, supervision/fallback strategies). Experience with AWS Bedrock and/or SageMaker (or equivalent managed ML/GenAI platforms) and deployment patterns for scalable inference. Experience with evaluation frameworks and approaches (golden datasets, LLM as judge, human in the loop review, red teaming). Experience fine tuning models (e.g., LoRA/QLoRA/DoRA) and/or working with SLMs, embeddings, and retrieval systems. Experience with developer productivity tooling such as GitHub Copilot and Claude Code, paired with strong SDLC controls. Knowledge of the financial services industry and operating in regulated environments (auditability, controls, data handling). Exposure to distributed compute/training concepts (e.g., DDP, sharding) and performance/cost optimization. We are an equal opportunity employer and place a high value on diversity and inclusion at our company. We do not discriminate on the basis of any protected attribute, including race, religion, color, national origin, gender, sexual orientation, gender identity, pregnancy or disability, or any other basis protected under applicable law. We also make reasonable accommodations for applicants and employees' religious practices and beliefs, as well as mental health or physical disability needs.
At Citi, we are pioneering the future of enterprise operations through innovative technology. Our COO-Technology Engineering and Architecture capability is at the forefront, responsible for architecting best in class solutions, driving end to end transformation, and integrating cutting edge Generative AI solutions to unlock unparalleled efficiency, automation, and risk reduction across our global operations. The Team: Innovating at Scale Our team is a dynamic hub of engineers and innovators dedicated to solving complex business challenges with intelligent solutions. We believe in building robust, scalable products that deliver tangible impact. We foster an environment of continuous learning, rapid iteration, and strong engineering practices. Here, you'll work alongside passionate experts, leverage the latest in AI, and contribute to a culture that values clean code, thoughtful design, and direct, hands on problem solving. We're not just adopting AI; we're building the intelligence that powers our enterprise. The Role: We are seeking an exceptional Staff Generative AI Engineer to join our team. This is a critical, deeply hands on role for a seasoned software engineer with a profound passion for Generative AI, Large Language Models (LLMs), and agentic frameworks. You will be instrumental in designing, building, and deploying real world, commercial production systems, not just proofs of concept. This is an Individual Contributor (IC) role with no direct people management responsibilities. Your expertise in containers (especially OpenShift), strong Python programming, and advanced LLM/agentic frameworks will be essential as you drive significant operational efficiencies and set new standards for engineering excellence. If you're a builder who thrives on technical challenge, delivering measurable impact, and mentoring others while getting your hands dirty with code, we want to hear from you. Architect & Build Production Systems: Lead the hands on development of sophisticated Generative AI applications, LLM powered solutions, and intricate agentic frameworks primarily using Python. Your code will be clean, performant, scalable, and deployed directly into commercial production environments, solving real business problems. Pioneer Automation with Agents: Design and implement intelligent agents capable of understanding, reasoning, and orchestrating complex workflows to automate critical enterprise business processes, driving efficiency and reducing operational risk at scale. Master Containerized Deployments: Demonstrate deep comfort and expertise with container technologies, particularly deploying and managing applications within OpenShift environments. Drive Technical Direction & Ownership: Contribute significantly to the technical strategy and roadmap for Generative AI adoption, influencing architectural decisions and technology choices across our product portfolio, ensuring all solutions are production ready. Champion Engineering Excellence: Instill and uphold rigorous software engineering best practices, including robust testing, code reviews, documentation, and continuous integration/delivery, ensuring the highest quality for our mission critical systems running in production. Innovate & Research: Stay at the bleeding edge of Generative AI, actively exploring new models, techniques, and frameworks. Contribute to both applied engineering and research initiatives within the domain. You will have access to state of the art AI assisted development tools like Devin and Copilot to amplify your productivity and creativity. Mentor & Collaborate: Act as a technical leader and mentor to junior engineers, fostering a culture of knowledge sharing and continuous improvement. Collaborate closely with cross functional teams, product managers, and stakeholders to deliver impactful solutions. Iterate & Deliver: Thrive in an agile, fast paced environment, prioritizing rapid delivery, iterative development, and adaptability. Focus on delivering measurable business value and learning quickly from prototypes and deployments, always with a path to production in mind. Ensure Responsible AI: Design and implement robust guardrails and ethical considerations into AI solutions, proactively assessing and mitigating risks in line with organizational and regulatory standards. Minimum Qualifications: 10+ years of professional software engineering experience, demonstrating a strong track record of designing, building, and delivering scalable enterprise grade solutions in commercial production environments, not just proofs of concept. Expert level proficiency in Python is a must have, with a deep understanding of its ecosystem for AI/ML development, data engineering, and backend services. Full stack development experience is a distinct advantage. Extensive hands on experience with Generative AI concepts, Large Language Models (LLMs), transformer architectures, RAG, and advanced agentic frameworks (e.g., LangChain, LangGraph, Google ADK. Optionally AutoGen, CrewAI, LlamaIndex, Semantic Kernel). Deep comfort and practical experience with containers and orchestration technologies, specifically OpenShift. Demonstrated ability to architect, develop, and deploy highly performant, large scale AI/ML systems into production environments. Strong understanding of modern software development principles, clean code practices, data structures, algorithms, and distributed systems. Proficiency with Relational (preferably, PostgreSQL) and Vector (preferably, pgvector) databases. Preferred Qualifications (Bonus Points): Proficiency in additional programming languages such as Java, JavaScript/TypeScript, or Golang. Experience with specific frameworks like Spring (AI, Boot), N8N, or Flask. Familiarity with messaging and integration platforms such as Kafka or JMS/MQ. Experience with UI development using modern frameworks like React JS or StreamLit for interactive AI applications. Practical experience in model risk management, developing AI guardrails, and establishing end user adoption pathways for Generative AI solutions. A proven track record of contributing to open source projects or publishing relevant research in AI/ML. Why You'll Love Working Here: Unprecedented Impact & Visibility: Contribute to critical, high visibility projects that are transforming a global enterprise, working on firm wide initiatives that directly influence our operational future. Cutting Edge Technology: Work with the latest Generative AI models, agentic frameworks, and cloud native technologies, enhanced by access to AI assisted development tools like Devin and Copilot. Growth & Development: A culture of continuous learning, mentorship, and opportunities to lead and innovate. Benefit from extensive learning resources including Udemy for Business and Pluralsight. Collaborative Environment: Join a highly skilled, passionate team that values collaboration, intellectual curiosity, and shared success. Flexible Work Environment: Embrace a hybrid working model, balancing productive in office collaboration (3 days) with the flexibility of working from home (up to 2 days). Global Scale: Build solutions that operate at a massive scale, impacting users and operations worldwide. Citi is an equal opportunity employer, and qualified candidates will receive consideration without regard to their race, color, religion, sex, sexual orientation, gender identity, national origin, disability, status as a protected veteran, or any other characteristic protected by law. If you are a person with a disability and need a reasonable accommodation to use our search tools and/or apply for a career opportunity review Accessibility at Citi. View Citi's EEO Policy Statement and the Know Your Rights poster.
25/07/2026
Full time
At Citi, we are pioneering the future of enterprise operations through innovative technology. Our COO-Technology Engineering and Architecture capability is at the forefront, responsible for architecting best in class solutions, driving end to end transformation, and integrating cutting edge Generative AI solutions to unlock unparalleled efficiency, automation, and risk reduction across our global operations. The Team: Innovating at Scale Our team is a dynamic hub of engineers and innovators dedicated to solving complex business challenges with intelligent solutions. We believe in building robust, scalable products that deliver tangible impact. We foster an environment of continuous learning, rapid iteration, and strong engineering practices. Here, you'll work alongside passionate experts, leverage the latest in AI, and contribute to a culture that values clean code, thoughtful design, and direct, hands on problem solving. We're not just adopting AI; we're building the intelligence that powers our enterprise. The Role: We are seeking an exceptional Staff Generative AI Engineer to join our team. This is a critical, deeply hands on role for a seasoned software engineer with a profound passion for Generative AI, Large Language Models (LLMs), and agentic frameworks. You will be instrumental in designing, building, and deploying real world, commercial production systems, not just proofs of concept. This is an Individual Contributor (IC) role with no direct people management responsibilities. Your expertise in containers (especially OpenShift), strong Python programming, and advanced LLM/agentic frameworks will be essential as you drive significant operational efficiencies and set new standards for engineering excellence. If you're a builder who thrives on technical challenge, delivering measurable impact, and mentoring others while getting your hands dirty with code, we want to hear from you. Architect & Build Production Systems: Lead the hands on development of sophisticated Generative AI applications, LLM powered solutions, and intricate agentic frameworks primarily using Python. Your code will be clean, performant, scalable, and deployed directly into commercial production environments, solving real business problems. Pioneer Automation with Agents: Design and implement intelligent agents capable of understanding, reasoning, and orchestrating complex workflows to automate critical enterprise business processes, driving efficiency and reducing operational risk at scale. Master Containerized Deployments: Demonstrate deep comfort and expertise with container technologies, particularly deploying and managing applications within OpenShift environments. Drive Technical Direction & Ownership: Contribute significantly to the technical strategy and roadmap for Generative AI adoption, influencing architectural decisions and technology choices across our product portfolio, ensuring all solutions are production ready. Champion Engineering Excellence: Instill and uphold rigorous software engineering best practices, including robust testing, code reviews, documentation, and continuous integration/delivery, ensuring the highest quality for our mission critical systems running in production. Innovate & Research: Stay at the bleeding edge of Generative AI, actively exploring new models, techniques, and frameworks. Contribute to both applied engineering and research initiatives within the domain. You will have access to state of the art AI assisted development tools like Devin and Copilot to amplify your productivity and creativity. Mentor & Collaborate: Act as a technical leader and mentor to junior engineers, fostering a culture of knowledge sharing and continuous improvement. Collaborate closely with cross functional teams, product managers, and stakeholders to deliver impactful solutions. Iterate & Deliver: Thrive in an agile, fast paced environment, prioritizing rapid delivery, iterative development, and adaptability. Focus on delivering measurable business value and learning quickly from prototypes and deployments, always with a path to production in mind. Ensure Responsible AI: Design and implement robust guardrails and ethical considerations into AI solutions, proactively assessing and mitigating risks in line with organizational and regulatory standards. Minimum Qualifications: 10+ years of professional software engineering experience, demonstrating a strong track record of designing, building, and delivering scalable enterprise grade solutions in commercial production environments, not just proofs of concept. Expert level proficiency in Python is a must have, with a deep understanding of its ecosystem for AI/ML development, data engineering, and backend services. Full stack development experience is a distinct advantage. Extensive hands on experience with Generative AI concepts, Large Language Models (LLMs), transformer architectures, RAG, and advanced agentic frameworks (e.g., LangChain, LangGraph, Google ADK. Optionally AutoGen, CrewAI, LlamaIndex, Semantic Kernel). Deep comfort and practical experience with containers and orchestration technologies, specifically OpenShift. Demonstrated ability to architect, develop, and deploy highly performant, large scale AI/ML systems into production environments. Strong understanding of modern software development principles, clean code practices, data structures, algorithms, and distributed systems. Proficiency with Relational (preferably, PostgreSQL) and Vector (preferably, pgvector) databases. Preferred Qualifications (Bonus Points): Proficiency in additional programming languages such as Java, JavaScript/TypeScript, or Golang. Experience with specific frameworks like Spring (AI, Boot), N8N, or Flask. Familiarity with messaging and integration platforms such as Kafka or JMS/MQ. Experience with UI development using modern frameworks like React JS or StreamLit for interactive AI applications. Practical experience in model risk management, developing AI guardrails, and establishing end user adoption pathways for Generative AI solutions. A proven track record of contributing to open source projects or publishing relevant research in AI/ML. Why You'll Love Working Here: Unprecedented Impact & Visibility: Contribute to critical, high visibility projects that are transforming a global enterprise, working on firm wide initiatives that directly influence our operational future. Cutting Edge Technology: Work with the latest Generative AI models, agentic frameworks, and cloud native technologies, enhanced by access to AI assisted development tools like Devin and Copilot. Growth & Development: A culture of continuous learning, mentorship, and opportunities to lead and innovate. Benefit from extensive learning resources including Udemy for Business and Pluralsight. Collaborative Environment: Join a highly skilled, passionate team that values collaboration, intellectual curiosity, and shared success. Flexible Work Environment: Embrace a hybrid working model, balancing productive in office collaboration (3 days) with the flexibility of working from home (up to 2 days). Global Scale: Build solutions that operate at a massive scale, impacting users and operations worldwide. Citi is an equal opportunity employer, and qualified candidates will receive consideration without regard to their race, color, religion, sex, sexual orientation, gender identity, national origin, disability, status as a protected veteran, or any other characteristic protected by law. If you are a person with a disability and need a reasonable accommodation to use our search tools and/or apply for a career opportunity review Accessibility at Citi. View Citi's EEO Policy Statement and the Know Your Rights poster.
Founding Security Engineer (Application & Infrastructure) Build the shield that makes Enterprise Superintelligence trustworthy London / Remote • Full-time • Pavo Labs About Pavo Pavo is building Enterprise Superintelligence: compounding systems that take ownership of business outcomes and work with humans to deliver them. We believe that while foundation models are necessary, they are not sufficient. The hard problem is systems intelligence: end-to-end architectures that understand a company's code, data, and decisions, and improve themselves through experience. We are assembling a small, senior team of researchers and engineers obsessed with systems-first intelligence. Our current team consists of PhDs and ML engineers from top applied ML and coding agent companies, with a heritage of shipping systems at Spotify, ShareChat, and Sourcegraph scale. Our team has built impressive momentum with a small group of highly capable engineers and researchers. The Opportunity As a Founding Security Engineer, you will help establish the security foundations for Pavo's agentic and knowledge systems. You help secure autonomous systems that write code, execute tools, and interact with sensitive enterprise data. This role sits at the bleeding edge of AI Security, wherein you harden the infrastructure that allows our knowledge and agentic systems to work safely inside Fortune 500 environments. You will build the shield that makes Enterprise Superintelligence trustworthy. What You'll Build You will own the holistic security posture of the Pavo platform, spanning Application, AI, and Infrastructure security: AI & Application Security: Lead the defense against LLM-specific vulnerabilities (Prompt Injection, Insecure Output Handling) and standard web threats (OWASP Top 10). Implement "Guardrails" that sanitize agent inputs/outputs and conduct continuous red-teaming of our agent behaviors. Secure SDLC & DevSecOps: Embed security into our CI/CD pipelines without slowing down our high-velocity engineering team. Integrate automated SAST/DAST scanning, dependency management (SCA), and secret detection into our daily workflow. Cloud & Infrastructure Hardening: Work closely with Systems Engineers to secure our Kubernetes clusters and compute environments. Design strict IAM policies (least privilege for agents) and ensure network isolation so that agent execution environments are impenetrable. Vulnerability Management: Own the lifecycle of vulnerability detection and remediation. Manage bug bounty programs, coordinate third-party pentests, and ensure our open-source dependencies (and the code our agents generate) are secure. Enterprise Trust: Help design features that give our customers confidence, such as audit logging, data residency controls, and rigorous access governance. What We Are Looking For We are looking for a security practitioner who is a builder at heart-someone who would rather ship a secure fix than write a policy document. Core Qualifications Experience: 5+ years of experience in Security Engineering, with a strong focus on Application Security and Cloud Security. AppSec Proficiency: Deep understanding of modern web vulnerabilities (CSRF, SSRF, XSS) and experience utilizing tools like Burp Suite, Semgrep, or CodeQL. Review code in Python or Go and spot logic flaws that scanners miss. AI Security Curiosity: Understand the unique risks of LLMs. Familiar with the OWASP Top 10 for LLMs and have explored defenses against prompt injection and data exfiltration in agentic systems. Cloud Native Security: Hands-on experience securing AWS/GCP environments and Kubernetes clusters. Knowledge of container security (capabilities, seccomp, namespaces) and how to secure microservices architectures. Offensive Mindset: Experience with Red Teaming or CTFs. Think like an attacker to uncover weaknesses in business logic and agent reasoning. Nice to Have Experience securing execution sandboxes (gVisor, Firecracker, or similar). Background in "Purple Teaming"-collaborating with developers to fix what you break. Contributions to the open-source security community or research on AI safety. Knowledge of compliance frameworks (SOC 2, ISO 27001) in an early-stage startup context. Why Join Us Founding Equity: Significant ownership in a company tackling the next layer of the AI stack. Frontier Security: Define the security standards for a new category of software-autonomous enterprise agents. World-Class Team: Collaborate with a dense talent cluster of researchers and engineers who have shipped products serving hundreds of millions of users. Pavo is an equal opportunity employer. We celebrate diversity and are committed to creating an inclusive environment for all employees.
25/07/2026
Full time
Founding Security Engineer (Application & Infrastructure) Build the shield that makes Enterprise Superintelligence trustworthy London / Remote • Full-time • Pavo Labs About Pavo Pavo is building Enterprise Superintelligence: compounding systems that take ownership of business outcomes and work with humans to deliver them. We believe that while foundation models are necessary, they are not sufficient. The hard problem is systems intelligence: end-to-end architectures that understand a company's code, data, and decisions, and improve themselves through experience. We are assembling a small, senior team of researchers and engineers obsessed with systems-first intelligence. Our current team consists of PhDs and ML engineers from top applied ML and coding agent companies, with a heritage of shipping systems at Spotify, ShareChat, and Sourcegraph scale. Our team has built impressive momentum with a small group of highly capable engineers and researchers. The Opportunity As a Founding Security Engineer, you will help establish the security foundations for Pavo's agentic and knowledge systems. You help secure autonomous systems that write code, execute tools, and interact with sensitive enterprise data. This role sits at the bleeding edge of AI Security, wherein you harden the infrastructure that allows our knowledge and agentic systems to work safely inside Fortune 500 environments. You will build the shield that makes Enterprise Superintelligence trustworthy. What You'll Build You will own the holistic security posture of the Pavo platform, spanning Application, AI, and Infrastructure security: AI & Application Security: Lead the defense against LLM-specific vulnerabilities (Prompt Injection, Insecure Output Handling) and standard web threats (OWASP Top 10). Implement "Guardrails" that sanitize agent inputs/outputs and conduct continuous red-teaming of our agent behaviors. Secure SDLC & DevSecOps: Embed security into our CI/CD pipelines without slowing down our high-velocity engineering team. Integrate automated SAST/DAST scanning, dependency management (SCA), and secret detection into our daily workflow. Cloud & Infrastructure Hardening: Work closely with Systems Engineers to secure our Kubernetes clusters and compute environments. Design strict IAM policies (least privilege for agents) and ensure network isolation so that agent execution environments are impenetrable. Vulnerability Management: Own the lifecycle of vulnerability detection and remediation. Manage bug bounty programs, coordinate third-party pentests, and ensure our open-source dependencies (and the code our agents generate) are secure. Enterprise Trust: Help design features that give our customers confidence, such as audit logging, data residency controls, and rigorous access governance. What We Are Looking For We are looking for a security practitioner who is a builder at heart-someone who would rather ship a secure fix than write a policy document. Core Qualifications Experience: 5+ years of experience in Security Engineering, with a strong focus on Application Security and Cloud Security. AppSec Proficiency: Deep understanding of modern web vulnerabilities (CSRF, SSRF, XSS) and experience utilizing tools like Burp Suite, Semgrep, or CodeQL. Review code in Python or Go and spot logic flaws that scanners miss. AI Security Curiosity: Understand the unique risks of LLMs. Familiar with the OWASP Top 10 for LLMs and have explored defenses against prompt injection and data exfiltration in agentic systems. Cloud Native Security: Hands-on experience securing AWS/GCP environments and Kubernetes clusters. Knowledge of container security (capabilities, seccomp, namespaces) and how to secure microservices architectures. Offensive Mindset: Experience with Red Teaming or CTFs. Think like an attacker to uncover weaknesses in business logic and agent reasoning. Nice to Have Experience securing execution sandboxes (gVisor, Firecracker, or similar). Background in "Purple Teaming"-collaborating with developers to fix what you break. Contributions to the open-source security community or research on AI safety. Knowledge of compliance frameworks (SOC 2, ISO 27001) in an early-stage startup context. Why Join Us Founding Equity: Significant ownership in a company tackling the next layer of the AI stack. Frontier Security: Define the security standards for a new category of software-autonomous enterprise agents. World-Class Team: Collaborate with a dense talent cluster of researchers and engineers who have shipped products serving hundreds of millions of users. Pavo is an equal opportunity employer. We celebrate diversity and are committed to creating an inclusive environment for all employees.
Senior AI Engineer Manager/Associate Director Capital Markets Location: Manchester Working pattern: Hybrid Salary: Compensation aligned to experience and seniority Ref: J13116 Senior AI Engineering professionals are required to support the design, build and delivery of advanced AI solutions within financial services and capital markets environments. This role would suit an experienced professional with a strong background in AI engineering and enterprise solution delivery within complex environments. You will play a key role in shaping AI strategy, leading teams and delivering enterprise AI solutions, helping organisations solve complex operational, technical and regulatory challenges through AI adoption at scale. You will work across multidisciplinary teams, collaborating with data scientists, architects, MLOps/LLMOps engineers, business stakeholders and senior leadership to design, deliver and scale AI products, agentic AI solutions and data driven applications. Key responsibilities: Building and deploying AI prototypes, products and production ready solutions Designing and implementing end to end AI solutions that integrate with enterprise systems Working with LLMs, prompt engineering, RAG patterns, embeddings and fine tuning Developing AI agents and agentic workflows using modern frameworks Working with vector databases, APIs and modern data platforms Supporting AI deployment, serving patterns, evaluation frameworks and integration design Using Python and SQL to build robust, scalable AI and data solutions Working with cloud platforms such as AWS, Azure, GCP or Databricks Supporting MLOps, LLMOps, CI/CD and software engineering best practice Collaborating with technical and non-technical stakeholders across complex programmes Helping identify technical, delivery, security, data privacy and regulatory risks Contributing to technical documentation, solution design and delivery planning Supporting AI implementation and scaling initiatives across complex environments Leading and developing teams, supporting capability growth through mentoring, coaching and creating a collaborative, high performing environment Experience Required: Strong Python and SQL experience Applied AI engineering, ML engineering or software engineering background Experience with LLMs, RAG, embeddings, prompt engineering or fine tuning Exposure to LangChain, LangGraph, Agent Development Kit or similar agent frameworks Experience with vector databases such as Pinecone, Chroma or similar API development experience, ideally with FastAPI or similar frameworks Knowledge of MLOps, LLMOps, CI/CD or production deployment practices Experience designing or supporting evaluation frameworks for AI or agentic systems Experience working with modern data architectures and cloud platforms Understanding of AI risk, governance, security and regulatory considerations Financial services experience within capital markets or broader banking environments This is a strong opportunity for an AI engineering professional who wants to work on high impact AI and data transformation programmes within complex financial services environments.
25/07/2026
Full time
Senior AI Engineer Manager/Associate Director Capital Markets Location: Manchester Working pattern: Hybrid Salary: Compensation aligned to experience and seniority Ref: J13116 Senior AI Engineering professionals are required to support the design, build and delivery of advanced AI solutions within financial services and capital markets environments. This role would suit an experienced professional with a strong background in AI engineering and enterprise solution delivery within complex environments. You will play a key role in shaping AI strategy, leading teams and delivering enterprise AI solutions, helping organisations solve complex operational, technical and regulatory challenges through AI adoption at scale. You will work across multidisciplinary teams, collaborating with data scientists, architects, MLOps/LLMOps engineers, business stakeholders and senior leadership to design, deliver and scale AI products, agentic AI solutions and data driven applications. Key responsibilities: Building and deploying AI prototypes, products and production ready solutions Designing and implementing end to end AI solutions that integrate with enterprise systems Working with LLMs, prompt engineering, RAG patterns, embeddings and fine tuning Developing AI agents and agentic workflows using modern frameworks Working with vector databases, APIs and modern data platforms Supporting AI deployment, serving patterns, evaluation frameworks and integration design Using Python and SQL to build robust, scalable AI and data solutions Working with cloud platforms such as AWS, Azure, GCP or Databricks Supporting MLOps, LLMOps, CI/CD and software engineering best practice Collaborating with technical and non-technical stakeholders across complex programmes Helping identify technical, delivery, security, data privacy and regulatory risks Contributing to technical documentation, solution design and delivery planning Supporting AI implementation and scaling initiatives across complex environments Leading and developing teams, supporting capability growth through mentoring, coaching and creating a collaborative, high performing environment Experience Required: Strong Python and SQL experience Applied AI engineering, ML engineering or software engineering background Experience with LLMs, RAG, embeddings, prompt engineering or fine tuning Exposure to LangChain, LangGraph, Agent Development Kit or similar agent frameworks Experience with vector databases such as Pinecone, Chroma or similar API development experience, ideally with FastAPI or similar frameworks Knowledge of MLOps, LLMOps, CI/CD or production deployment practices Experience designing or supporting evaluation frameworks for AI or agentic systems Experience working with modern data architectures and cloud platforms Understanding of AI risk, governance, security and regulatory considerations Financial services experience within capital markets or broader banking environments This is a strong opportunity for an AI engineering professional who wants to work on high impact AI and data transformation programmes within complex financial services environments.
At Citi, we are pioneering the future of enterprise operations through innovative technology. Our COO-Technology Engineering and Architecture capability is at the forefront, responsible for architecting best-in-class solutions, driving end-to-end transformation, and integrating cutting-edge Generative AI solutions to unlock unparalleled efficiency, automation, and risk reduction across our global operations. The Team: Innovating at Scale Our team is a dynamic hub of engineers and innovators dedicated to solving complex business challenges with intelligent solutions. We believe in building robust, scalable products that deliver tangible impact. We foster an environment of continuous learning, rapid iteration, and strong engineering practices. Here, you'll work alongside passionate experts, leverage the latest in AI, and contribute to a culture that values clean code, thoughtful design, and direct, hands on problem solving. We're not just adopting AI; we're building the intelligence that powers our enterprise. The Role: We are seeking an exceptional Staff Generative AI Engineer to join our team. This is a critical, deeply hands on role for a seasoned software engineer with a profound passion for Generative AI, Large Language Models (LLMs), and agentic frameworks. You will be instrumental in designing, building, and deploying real world, commercial production systems, not just proofs of concept. This is an Individual Contributor (IC) role with no direct people management responsibilities. Your expertise in containers (especially OpenShift), strong Python programming, and advanced LLM/agentic frameworks will be essential as you drive significant operational efficiencies and set new standards for engineering excellence. If you're a builder who thrives on technical challenge, delivering measurable impact, and mentoring others while getting your hands dirty with code, we want to hear from you. Key Responsibilities: Architect & Build Production Systems: Lead the hands on development of sophisticated Generative AI applications, LLM powered solutions, and intricate agentic frameworks primarily using Python. Your code will be clean, performant, scalable, and deployed directly into commercial production environments, solving real business problems. Pioneer Automation with Agents: Design and implement intelligent agents capable of understanding, reasoning, and orchestrating complex workflows to automate critical enterprise business processes, driving efficiency and reducing operational risk at scale. Master Containerized Deployments: Demonstrate deep comfort and expertise with container technologies, particularly deploying and managing applications within OpenShift environments. Drive Technical Direction & Ownership: Contribute significantly to the technical strategy and roadmap for Generative AI adoption, influencing architectural decisions and technology choices across our product portfolio, ensuring all solutions are production ready. Champion Engineering Excellence: Instill and uphold rigorous software engineering best practices, including robust testing, code reviews, documentation, and continuous integration/delivery, ensuring the highest quality for our mission critical systems running in production. Innovate & Research: Stay at the bleeding edge of Generative AI, actively exploring new models, techniques, and frameworks. Contribute to both applied engineering and research initiatives within the domain. You will have access to state of the art AI assisted development tools like Devin and Copilot to amplify your productivity and creativity. Mentor & Collaborate: Act as a technical leader and mentor to junior engineers, fostering a culture of knowledge sharing and continuous improvement. Collaborate closely with cross functional teams, product managers, and stakeholders to deliver impactful solutions. Iterate & Deliver: Thrive in an agile, fast paced environment, prioritizing rapid delivery, iterative development, and adaptability. Focus on delivering measurable business value and learning quickly from prototypes and deployments, always with a path to production in mind. Ensure Responsible AI: Design and implement robust guardrails and ethical considerations into AI solutions, proactively assessing and mitigating risks in line with organizational and regulatory standards. Minimum Qualifications: 10+ years of professional software engineering experience, demonstrating a strong track record of designing, building, and delivering scalable enterprise grade solutions in commercial production environments, not just proofs of concept. Expert level proficiency in Python is a must have, with a deep understanding of its ecosystem for AI/ML development, data engineering, and backend services. Full stack development experience is a distinct advantage. Extensive hands on experience with Generative AI concepts, Large Language Models (LLMs), transformer architectures, RAG, and advanced agentic frameworks (e.g., LangChain, LangGraph, Google ADK. Optionally AutoGen, CrewAI, LlamaIndex, Semantic Kernel). Deep comfort and practical experience with containers and orchestration technologies, specifically OpenShift. Demonstrated ability to architect, develop, and deploy highly performant, large scale AI/ML systems into production environments. Strong understanding of modern software development principles, clean code practices, data structures, algorithms, and distributed systems. Proficiency with Relational (preferably, PostgreSQL) and Vector (preferably, pgvector) databases. Preferred Qualifications (Bonus Points): Proficiency in additional programming languages such as Java, JavaScript/TypeScript, or Golang. Experience with specific frameworks like Spring (AI, Boot), N8N, or Flask. Familiarity with messaging and integration platforms such as Kafka or JMS/MQ. Experience with UI development using modern frameworks like React JS or StreamLit for interactive AI applications. Practical experience in model risk management, developing AI guardrails, and establishing end user adoption pathways for Generative AI solutions. A proven track record of contributing to open source projects or publishing relevant research in AI/ML. Why You'll Love Working Here: Unprecedented Impact & Visibility: Contribute to critical, high visibility projects that are transforming a global enterprise, working on firm wide initiatives that directly influence our operational future. Cutting Edge Technology: Work with the latest Generative AI models, agentic frameworks, and cloud native technologies, enhanced by access to AI assisted development tools like Devin and Copilot. Growth & Development: A culture of continuous learning, mentorship, and opportunities to lead and innovate. Benefit from extensive learning resources including Udemy for Business and Pluralsight. Collaborative Environment: Join a highly skilled, passionate team that values collaboration, intellectual curiosity, and shared success. Flexible Work Environment: Embrace a hybrid working model, balancing productive in office collaboration (3 days) with the flexibility of working from home (up to 2 days). Global Scale: Build solutions that operate at a massive scale, impacting users and operations worldwide. Join us to build the future of intelligent enterprise solutions! Citi is an equal opportunity employer, and qualified candidates will receive consideration without regard to their race, color, religion, sex, sexual orientation, gender identity, national origin, disability, status as a protected veteran, or any other characteristic protected by law. If you are a person with a disability and need a reasonable accommodation to use our search tools and/or apply for a career opportunity review Accessibility at Citi. View Citi's EEO Policy Statement and the Know Your Rights poster.
24/07/2026
Full time
At Citi, we are pioneering the future of enterprise operations through innovative technology. Our COO-Technology Engineering and Architecture capability is at the forefront, responsible for architecting best-in-class solutions, driving end-to-end transformation, and integrating cutting-edge Generative AI solutions to unlock unparalleled efficiency, automation, and risk reduction across our global operations. The Team: Innovating at Scale Our team is a dynamic hub of engineers and innovators dedicated to solving complex business challenges with intelligent solutions. We believe in building robust, scalable products that deliver tangible impact. We foster an environment of continuous learning, rapid iteration, and strong engineering practices. Here, you'll work alongside passionate experts, leverage the latest in AI, and contribute to a culture that values clean code, thoughtful design, and direct, hands on problem solving. We're not just adopting AI; we're building the intelligence that powers our enterprise. The Role: We are seeking an exceptional Staff Generative AI Engineer to join our team. This is a critical, deeply hands on role for a seasoned software engineer with a profound passion for Generative AI, Large Language Models (LLMs), and agentic frameworks. You will be instrumental in designing, building, and deploying real world, commercial production systems, not just proofs of concept. This is an Individual Contributor (IC) role with no direct people management responsibilities. Your expertise in containers (especially OpenShift), strong Python programming, and advanced LLM/agentic frameworks will be essential as you drive significant operational efficiencies and set new standards for engineering excellence. If you're a builder who thrives on technical challenge, delivering measurable impact, and mentoring others while getting your hands dirty with code, we want to hear from you. Key Responsibilities: Architect & Build Production Systems: Lead the hands on development of sophisticated Generative AI applications, LLM powered solutions, and intricate agentic frameworks primarily using Python. Your code will be clean, performant, scalable, and deployed directly into commercial production environments, solving real business problems. Pioneer Automation with Agents: Design and implement intelligent agents capable of understanding, reasoning, and orchestrating complex workflows to automate critical enterprise business processes, driving efficiency and reducing operational risk at scale. Master Containerized Deployments: Demonstrate deep comfort and expertise with container technologies, particularly deploying and managing applications within OpenShift environments. Drive Technical Direction & Ownership: Contribute significantly to the technical strategy and roadmap for Generative AI adoption, influencing architectural decisions and technology choices across our product portfolio, ensuring all solutions are production ready. Champion Engineering Excellence: Instill and uphold rigorous software engineering best practices, including robust testing, code reviews, documentation, and continuous integration/delivery, ensuring the highest quality for our mission critical systems running in production. Innovate & Research: Stay at the bleeding edge of Generative AI, actively exploring new models, techniques, and frameworks. Contribute to both applied engineering and research initiatives within the domain. You will have access to state of the art AI assisted development tools like Devin and Copilot to amplify your productivity and creativity. Mentor & Collaborate: Act as a technical leader and mentor to junior engineers, fostering a culture of knowledge sharing and continuous improvement. Collaborate closely with cross functional teams, product managers, and stakeholders to deliver impactful solutions. Iterate & Deliver: Thrive in an agile, fast paced environment, prioritizing rapid delivery, iterative development, and adaptability. Focus on delivering measurable business value and learning quickly from prototypes and deployments, always with a path to production in mind. Ensure Responsible AI: Design and implement robust guardrails and ethical considerations into AI solutions, proactively assessing and mitigating risks in line with organizational and regulatory standards. Minimum Qualifications: 10+ years of professional software engineering experience, demonstrating a strong track record of designing, building, and delivering scalable enterprise grade solutions in commercial production environments, not just proofs of concept. Expert level proficiency in Python is a must have, with a deep understanding of its ecosystem for AI/ML development, data engineering, and backend services. Full stack development experience is a distinct advantage. Extensive hands on experience with Generative AI concepts, Large Language Models (LLMs), transformer architectures, RAG, and advanced agentic frameworks (e.g., LangChain, LangGraph, Google ADK. Optionally AutoGen, CrewAI, LlamaIndex, Semantic Kernel). Deep comfort and practical experience with containers and orchestration technologies, specifically OpenShift. Demonstrated ability to architect, develop, and deploy highly performant, large scale AI/ML systems into production environments. Strong understanding of modern software development principles, clean code practices, data structures, algorithms, and distributed systems. Proficiency with Relational (preferably, PostgreSQL) and Vector (preferably, pgvector) databases. Preferred Qualifications (Bonus Points): Proficiency in additional programming languages such as Java, JavaScript/TypeScript, or Golang. Experience with specific frameworks like Spring (AI, Boot), N8N, or Flask. Familiarity with messaging and integration platforms such as Kafka or JMS/MQ. Experience with UI development using modern frameworks like React JS or StreamLit for interactive AI applications. Practical experience in model risk management, developing AI guardrails, and establishing end user adoption pathways for Generative AI solutions. A proven track record of contributing to open source projects or publishing relevant research in AI/ML. Why You'll Love Working Here: Unprecedented Impact & Visibility: Contribute to critical, high visibility projects that are transforming a global enterprise, working on firm wide initiatives that directly influence our operational future. Cutting Edge Technology: Work with the latest Generative AI models, agentic frameworks, and cloud native technologies, enhanced by access to AI assisted development tools like Devin and Copilot. Growth & Development: A culture of continuous learning, mentorship, and opportunities to lead and innovate. Benefit from extensive learning resources including Udemy for Business and Pluralsight. Collaborative Environment: Join a highly skilled, passionate team that values collaboration, intellectual curiosity, and shared success. Flexible Work Environment: Embrace a hybrid working model, balancing productive in office collaboration (3 days) with the flexibility of working from home (up to 2 days). Global Scale: Build solutions that operate at a massive scale, impacting users and operations worldwide. Join us to build the future of intelligent enterprise solutions! Citi is an equal opportunity employer, and qualified candidates will receive consideration without regard to their race, color, religion, sex, sexual orientation, gender identity, national origin, disability, status as a protected veteran, or any other characteristic protected by law. If you are a person with a disability and need a reasonable accommodation to use our search tools and/or apply for a career opportunity review Accessibility at Citi. View Citi's EEO Policy Statement and the Know Your Rights poster.
About Scrumconnect Consulting Scrumconnect Consulting is a multi-award-winning digital consultancy, recognised for delivering impactful and innovative technology solutions across UK government departments. Our work has positively influenced the lives of over 40 million UK citizens. We are passionate about user-centred design, agile delivery, and building digital services that make a real difference - and we're now scaling that expertise into large, high-stakes AI adoption programmes across the public sector. Overview We're looking for a Lead AI Engineer to be the hands-on technical builder at the core of a large-scale AI Operating Model programme for a central government department. Where the Lead Technical Architect sets direction, you turn it into working, production-grade systems - semantic search, RAG pipelines, and broader generative AI capability - integrated into complex Legacy and multi-cloud environments handling high-volume, sensitive public sector data. You'll work inside a collaborative "Rainbow Team" alongside civil servants and the wider delivery team, staying close to the code while also mentoring engineers and helping build the internal capability the department needs to eventually run these systems without long-term reliance on external suppliers. Key Responsibilities Hands-On Build & Delivery Design, build, and ship production AI components - RAG pipelines, retrieval and embedding infrastructure, orchestration logic, and integration layers - writing high-quality, tested, maintainable code and staying close to implementation rather than delegating it away. Technical Leadership Within the Squad Lead the engineering practice within your delivery team: set coding standards, review designs and pull requests, unblock technically complex problems, and mentor other engineers day to day. Responsible AI in Practice Implement the guardrails the Architect designs - bias mitigation checks, evaluation harnesses, human-in-the-loop review points - so that Responsible AI principles (ATRS alignment, NCSC "Secure by Design, " meaningful human control) are enforced in the running system, not just on paper. Reliability, Security & Observability Build AI services to be secure-by-default and observable in production: logging, monitoring, alerting, and rollback paths appropriate for sensitive public-sector data and high-availability requirements. Knowledge Transfer & Capability Uplift Work within the OKUA (Ownership, Knowledge, Understanding, Awareness) framework and "Docs-as-Code" practices to pair with and upskill internal government engineers, so capability genuinely transfers rather than staying locked in the consultancy team. Efficient, Sustainable Engineering Favour low-modality, resource-efficient designs where they meet the need - right-sizing models and infrastructure rather than defaulting to the largest/most expensive option - in line with the programme's Green AI and Net Zero commitments. Required Skills & Experience Loosely mapped to the Government Digital and Data (DDaT) framework, at Lead Engineer level: - Coding and Scripting (Expert) - writing production-grade, well-tested code; setting standards for others; comfortable owning components end-to-end. - Systems Design (Practitioner) - designing components that integrate cleanly into a wider, architect-defined system; understanding trade-offs across the stack. - Data Engineering (Practitioner) - building reliable pipelines to ingest, clean, and prepare data (including unstructured/Legacy sources) for AI consumption. - DevOps/Continuous Delivery (Practitioner) - CI/CD pipelines, infrastructure-as-code, and automated deployment for AI workloads specifically (not just conventional web services). - Testing & Evaluation (Practitioner) - beyond conventional unit/integration testing, building evaluation harnesses for AI system quality: retrieval accuracy, hallucination rate, bias/fairness checks. - Problem Solving (Practitioner) - diagnosing and resolving complex, ambiguous technical issues under production pressure. - Agile Working (Practitioner) - delivering iteratively within a blended, multidisciplinary team including civil servants. Given the scale of this programme, direct hands-on depth across the AI engineering stack is essential: - Strong general-purpose programming (most commonly Python) applied to AI/ML systems - Semantic search, vector/embedding infrastructure, and RAG pipeline construction - LLM orchestration and agentic frameworks (eg LangChain/LlamaIndex-style tooling, multi-agent patterns) - Prompt engineering and systematic evaluation/guardrail tooling (hallucination detection, safety testing) - LLMOps/MLOps - model versioning, deployment, monitoring, and rollback for AI services in production - Cloud-native engineering across major providers (AWS, Azure, or GCP), including their AI/ML tooling - Containerisation and infrastructure-as-code for repeatable, auditable deployments - Secure-by-design engineering appropriate to sensitive public-sector data Desirable Experience - AWS/Azure/GCP certifications (associate or professional level) - Prior delivery of AI or digital services within UK central government or wider public sector - Experience fine-tuning or adapting open-source/foundation models for a specific domain - Open-source contributions or active engagement in AI/ML engineering communities - Experience designing for sustainability/Green IT commitments - The technological capabilities can span a wide range of AI and automation tools, including Virtual Assistants, Robotic Process Automation (RPA), Computer Vision, Natural Language Processing (NLP), Machine Learning, Deep Learning, Generative AI, Frontier LLMs, and Predictive AI. A strong candidate would have experience/exposure to nuances of these tools/technologies. Location and Working Pattern Hybrid, based from Newcastle upon Tyne, with on-site attendance required for workshops, knowledge-transfer sessions, and onboarding. All production system and data access must be performed solely from within the UK. How We Work Our values: - Collaboration - we are stronger as a team than as individuals; we tackle problems and celebrate wins together. - Create Value Early - we find the quickest route from idea to product, because our clients rely on us to do what's best. - Integrity - teamwork requires trust; we can always be relied upon to uphold the highest standards. - Commitment - no matter what, no matter how, we give our 100% to keeping our promises and achieving our goals. - Diversity and Inclusion - we believe diversity drives innovation and better outcomes, and we're committed to an inclusive environment where every individual is valued, respected, and supported. We welcome applications from candidates of all backgrounds, including women, people with disabilities, and diverse communities, as well as those seeking flexible working arrangements. As a Disability Confident Level 1 employer, we provide reasonable adjustments throughout recruitment and employment to ensure equal opportunity for all. How to Apply Please submit your CV. Shortlisted candidates will be invited to interview. This role requires BPSS (Baseline Personnel Security Standard) clearance - please flag in your application if you already hold clearance.
24/07/2026
Full time
About Scrumconnect Consulting Scrumconnect Consulting is a multi-award-winning digital consultancy, recognised for delivering impactful and innovative technology solutions across UK government departments. Our work has positively influenced the lives of over 40 million UK citizens. We are passionate about user-centred design, agile delivery, and building digital services that make a real difference - and we're now scaling that expertise into large, high-stakes AI adoption programmes across the public sector. Overview We're looking for a Lead AI Engineer to be the hands-on technical builder at the core of a large-scale AI Operating Model programme for a central government department. Where the Lead Technical Architect sets direction, you turn it into working, production-grade systems - semantic search, RAG pipelines, and broader generative AI capability - integrated into complex Legacy and multi-cloud environments handling high-volume, sensitive public sector data. You'll work inside a collaborative "Rainbow Team" alongside civil servants and the wider delivery team, staying close to the code while also mentoring engineers and helping build the internal capability the department needs to eventually run these systems without long-term reliance on external suppliers. Key Responsibilities Hands-On Build & Delivery Design, build, and ship production AI components - RAG pipelines, retrieval and embedding infrastructure, orchestration logic, and integration layers - writing high-quality, tested, maintainable code and staying close to implementation rather than delegating it away. Technical Leadership Within the Squad Lead the engineering practice within your delivery team: set coding standards, review designs and pull requests, unblock technically complex problems, and mentor other engineers day to day. Responsible AI in Practice Implement the guardrails the Architect designs - bias mitigation checks, evaluation harnesses, human-in-the-loop review points - so that Responsible AI principles (ATRS alignment, NCSC "Secure by Design, " meaningful human control) are enforced in the running system, not just on paper. Reliability, Security & Observability Build AI services to be secure-by-default and observable in production: logging, monitoring, alerting, and rollback paths appropriate for sensitive public-sector data and high-availability requirements. Knowledge Transfer & Capability Uplift Work within the OKUA (Ownership, Knowledge, Understanding, Awareness) framework and "Docs-as-Code" practices to pair with and upskill internal government engineers, so capability genuinely transfers rather than staying locked in the consultancy team. Efficient, Sustainable Engineering Favour low-modality, resource-efficient designs where they meet the need - right-sizing models and infrastructure rather than defaulting to the largest/most expensive option - in line with the programme's Green AI and Net Zero commitments. Required Skills & Experience Loosely mapped to the Government Digital and Data (DDaT) framework, at Lead Engineer level: - Coding and Scripting (Expert) - writing production-grade, well-tested code; setting standards for others; comfortable owning components end-to-end. - Systems Design (Practitioner) - designing components that integrate cleanly into a wider, architect-defined system; understanding trade-offs across the stack. - Data Engineering (Practitioner) - building reliable pipelines to ingest, clean, and prepare data (including unstructured/Legacy sources) for AI consumption. - DevOps/Continuous Delivery (Practitioner) - CI/CD pipelines, infrastructure-as-code, and automated deployment for AI workloads specifically (not just conventional web services). - Testing & Evaluation (Practitioner) - beyond conventional unit/integration testing, building evaluation harnesses for AI system quality: retrieval accuracy, hallucination rate, bias/fairness checks. - Problem Solving (Practitioner) - diagnosing and resolving complex, ambiguous technical issues under production pressure. - Agile Working (Practitioner) - delivering iteratively within a blended, multidisciplinary team including civil servants. Given the scale of this programme, direct hands-on depth across the AI engineering stack is essential: - Strong general-purpose programming (most commonly Python) applied to AI/ML systems - Semantic search, vector/embedding infrastructure, and RAG pipeline construction - LLM orchestration and agentic frameworks (eg LangChain/LlamaIndex-style tooling, multi-agent patterns) - Prompt engineering and systematic evaluation/guardrail tooling (hallucination detection, safety testing) - LLMOps/MLOps - model versioning, deployment, monitoring, and rollback for AI services in production - Cloud-native engineering across major providers (AWS, Azure, or GCP), including their AI/ML tooling - Containerisation and infrastructure-as-code for repeatable, auditable deployments - Secure-by-design engineering appropriate to sensitive public-sector data Desirable Experience - AWS/Azure/GCP certifications (associate or professional level) - Prior delivery of AI or digital services within UK central government or wider public sector - Experience fine-tuning or adapting open-source/foundation models for a specific domain - Open-source contributions or active engagement in AI/ML engineering communities - Experience designing for sustainability/Green IT commitments - The technological capabilities can span a wide range of AI and automation tools, including Virtual Assistants, Robotic Process Automation (RPA), Computer Vision, Natural Language Processing (NLP), Machine Learning, Deep Learning, Generative AI, Frontier LLMs, and Predictive AI. A strong candidate would have experience/exposure to nuances of these tools/technologies. Location and Working Pattern Hybrid, based from Newcastle upon Tyne, with on-site attendance required for workshops, knowledge-transfer sessions, and onboarding. All production system and data access must be performed solely from within the UK. How We Work Our values: - Collaboration - we are stronger as a team than as individuals; we tackle problems and celebrate wins together. - Create Value Early - we find the quickest route from idea to product, because our clients rely on us to do what's best. - Integrity - teamwork requires trust; we can always be relied upon to uphold the highest standards. - Commitment - no matter what, no matter how, we give our 100% to keeping our promises and achieving our goals. - Diversity and Inclusion - we believe diversity drives innovation and better outcomes, and we're committed to an inclusive environment where every individual is valued, respected, and supported. We welcome applications from candidates of all backgrounds, including women, people with disabilities, and diverse communities, as well as those seeking flexible working arrangements. As a Disability Confident Level 1 employer, we provide reasonable adjustments throughout recruitment and employment to ensure equal opportunity for all. How to Apply Please submit your CV. Shortlisted candidates will be invited to interview. This role requires BPSS (Baseline Personnel Security Standard) clearance - please flag in your application if you already hold clearance.
Senior Staff Generative AI Engineer - VP (IC, Hands-On)Applylocations: London United Kingdomtime type: Full timeposted on: Posted Todayjob requisition id: At Citi, we are pioneering the future of enterprise operations through innovative technology. Our COO-Technology Engineering and Architecture capability is at the forefront, responsible for architecting best-in-class solutions, driving end-to-end transformation, and integrating cutting-edge Generative AI solutions to unlock unparalleled efficiency, automation, and risk reduction across our global operations. The Team: Innovating at Scale Our team is a dynamic hub of engineers and innovators dedicated to solving complex business challenges with intelligent solutions. We believe in building robust, scalable products that deliver tangible impact. We foster an environment of continuous learning, rapid iteration, and strong engineering practices. Here, you'll work alongside passionate experts, leverage the latest in AI, and contribute to a culture that values clean code, thoughtful design, and direct, hands-on problem-solving. We're not just adopting AI; we're building the intelligence that powers our enterprise. The Role: We are seeking an exceptional Staff Generative AI Engineer to join our team. This is a critical, deeply hands-on role for a seasoned software engineer with a profound passion for Generative AI, Large Language Models (LLMs), and agentic frameworks. You will be instrumental in designing, building, and deploying real-world, commercial production systems , not just proofs-of-concept.This is an Individual Contributor (IC) role with no direct people management responsibilities.Your expertise in containers (especially OpenShift), strong Python programming, and advanced LLM/agentic frameworks will be essential as you drive significant operational efficiencies and set new standards for engineering excellence. If you're a builder who thrives on technical challenge, delivering measurable impact, and mentoring others while getting your hands dirty with code, we want to hear from you.As a Staff Generative AI Engineer, you will: Architect & Build Production Systems: Lead the hands-on development of sophisticated Generative AI applications, LLM-powered solutions, and intricate agentic frameworks primarily using Python . Your code will be clean, performant, scalable, and deployed directly into commercial production environments, solving real business problems. Pioneer Automation with Agents: Design and implement intelligent agents capable of understanding, reasoning, and orchestrating complex workflows to automate critical enterprise business processes, driving efficiency and reducing operational risk at scale. Master Containerized Deployments: Demonstrate deep comfort and expertise with container technologies, particularly deploying and managing applications within OpenShift environments. Drive Technical Direction & Ownership: Contribute significantly to the technical strategy and roadmap for Generative AI adoption, influencing architectural decisions and technology choices across our product portfolio, ensuring all solutions are production-ready. Champion Engineering Excellence: Instill and uphold rigorous software engineering best practices, including robust testing, code reviews, documentation, and continuous integration/delivery, ensuring the highest quality for our mission-critical systems running in production. Innovate & Research: Stay at the bleeding edge of Generative AI, actively exploring new models, techniques, and frameworks. Contribute to both applied engineering and research initiatives within the domain. You will have access to state-of-the-art AI-assisted development tools like Devin and Copilot to amplify your productivity and creativity. Mentor & Collaborate: Act as a technical leader and mentor to junior engineers, fostering a culture of knowledge sharing and continuous improvement. Collaborate closely with cross-functional teams, product managers, and stakeholders to deliver impactful solutions. Iterate & Deliver: Thrive in an agile, fast-paced environment, prioritizing rapid delivery, iterative development, and adaptability. Focus on delivering measurable business value and learning quickly from prototypes and deployments, always with a path to production in mind. Ensure Responsible AI: Design and implement robust guardrails and ethical considerations into AI solutions, proactively assessing and mitigating risks in line with organizational and regulatory standards. Minimum Qualifications: 10+ years of professional software engineering experience, demonstrating a strong track record of designing, building, and delivering scalable enterprise-grade solutions in commercial production environments, not just proofs-of-concept. Expert-level proficiency in Python is a must-have , with a deep understanding of its ecosystem for AI/ML development, data engineering, and backend services. Full-stack development experience is a distinct advantage. Extensive hands-on experience with Generative AI concepts, Large Language Models (LLMs), transformer architectures, RAG, and advanced agentic frameworks (e.g., LangChain, LangGraph, Google ADK. Optionally AutoGen, CrewAI, LlamaIndex, Semantic Kernel). Deep comfort and practical experience with containers and orchestration technologies, specifically OpenShift . Demonstrated ability to architect, develop, and deploy highly performant, large-scale AI/ML systems into production environments. Strong understanding of modern software development principles, clean code practices, data structures, algorithms, and distributed systems. Proficiency with Relational (preferably, PostgreSQL) and Vector (preferably, pgvector) databases. Preferred Qualifications (Bonus Points): Proficiency in additional programming languages such as Java, JavaScript/TypeScript, or Golang. Experience with specific frameworks like Spring (AI, Boot), N8N, or Flask. Familiarity with messaging and integration platforms such as Kafka or JMS/MQ. Experience with UI development using modern frameworks like React JS or StreamLit for interactive AI applications. Practical experience in model risk management, developing AI guardrails, and establishing end-user adoption pathways for Generative AI solutions. A proven track record of contributing to open-source projects or publishing relevant research in AI/ML. Why You'll Love Working Here: Unprecedented Impact & Visibility: Contribute to critical, high-visibility projects that are transforming a global enterprise, working on firm-wide initiatives that directly influence our operational future. Cutting-Edge Technology: Work with the latest Generative AI models, agentic frameworks, and cloud-native technologies, enhanced by access to AI-assisted development tools like Devin and Copilot . Growth & Development: A culture of continuous learning, mentorship, and opportunities to lead and innovate. Benefit from extensive learning resources including Udemy for Business and Pluralsight . Collaborative Environment: Join a highly skilled, passionate team that values collaboration, intellectual curiosity, and shared success. Flexible Work Environment: Embrace a hybrid working model, balancing productive in-office collaboration (3 days) with the flexibility of working from home (up to 2 days). Global Scale: Build solutions that operate at a massive scale, impacting users and operations worldwide.Join us to build the future of intelligent enterprise solutions!
24/07/2026
Full time
Senior Staff Generative AI Engineer - VP (IC, Hands-On)Applylocations: London United Kingdomtime type: Full timeposted on: Posted Todayjob requisition id: At Citi, we are pioneering the future of enterprise operations through innovative technology. Our COO-Technology Engineering and Architecture capability is at the forefront, responsible for architecting best-in-class solutions, driving end-to-end transformation, and integrating cutting-edge Generative AI solutions to unlock unparalleled efficiency, automation, and risk reduction across our global operations. The Team: Innovating at Scale Our team is a dynamic hub of engineers and innovators dedicated to solving complex business challenges with intelligent solutions. We believe in building robust, scalable products that deliver tangible impact. We foster an environment of continuous learning, rapid iteration, and strong engineering practices. Here, you'll work alongside passionate experts, leverage the latest in AI, and contribute to a culture that values clean code, thoughtful design, and direct, hands-on problem-solving. We're not just adopting AI; we're building the intelligence that powers our enterprise. The Role: We are seeking an exceptional Staff Generative AI Engineer to join our team. This is a critical, deeply hands-on role for a seasoned software engineer with a profound passion for Generative AI, Large Language Models (LLMs), and agentic frameworks. You will be instrumental in designing, building, and deploying real-world, commercial production systems , not just proofs-of-concept.This is an Individual Contributor (IC) role with no direct people management responsibilities.Your expertise in containers (especially OpenShift), strong Python programming, and advanced LLM/agentic frameworks will be essential as you drive significant operational efficiencies and set new standards for engineering excellence. If you're a builder who thrives on technical challenge, delivering measurable impact, and mentoring others while getting your hands dirty with code, we want to hear from you.As a Staff Generative AI Engineer, you will: Architect & Build Production Systems: Lead the hands-on development of sophisticated Generative AI applications, LLM-powered solutions, and intricate agentic frameworks primarily using Python . Your code will be clean, performant, scalable, and deployed directly into commercial production environments, solving real business problems. Pioneer Automation with Agents: Design and implement intelligent agents capable of understanding, reasoning, and orchestrating complex workflows to automate critical enterprise business processes, driving efficiency and reducing operational risk at scale. Master Containerized Deployments: Demonstrate deep comfort and expertise with container technologies, particularly deploying and managing applications within OpenShift environments. Drive Technical Direction & Ownership: Contribute significantly to the technical strategy and roadmap for Generative AI adoption, influencing architectural decisions and technology choices across our product portfolio, ensuring all solutions are production-ready. Champion Engineering Excellence: Instill and uphold rigorous software engineering best practices, including robust testing, code reviews, documentation, and continuous integration/delivery, ensuring the highest quality for our mission-critical systems running in production. Innovate & Research: Stay at the bleeding edge of Generative AI, actively exploring new models, techniques, and frameworks. Contribute to both applied engineering and research initiatives within the domain. You will have access to state-of-the-art AI-assisted development tools like Devin and Copilot to amplify your productivity and creativity. Mentor & Collaborate: Act as a technical leader and mentor to junior engineers, fostering a culture of knowledge sharing and continuous improvement. Collaborate closely with cross-functional teams, product managers, and stakeholders to deliver impactful solutions. Iterate & Deliver: Thrive in an agile, fast-paced environment, prioritizing rapid delivery, iterative development, and adaptability. Focus on delivering measurable business value and learning quickly from prototypes and deployments, always with a path to production in mind. Ensure Responsible AI: Design and implement robust guardrails and ethical considerations into AI solutions, proactively assessing and mitigating risks in line with organizational and regulatory standards. Minimum Qualifications: 10+ years of professional software engineering experience, demonstrating a strong track record of designing, building, and delivering scalable enterprise-grade solutions in commercial production environments, not just proofs-of-concept. Expert-level proficiency in Python is a must-have , with a deep understanding of its ecosystem for AI/ML development, data engineering, and backend services. Full-stack development experience is a distinct advantage. Extensive hands-on experience with Generative AI concepts, Large Language Models (LLMs), transformer architectures, RAG, and advanced agentic frameworks (e.g., LangChain, LangGraph, Google ADK. Optionally AutoGen, CrewAI, LlamaIndex, Semantic Kernel). Deep comfort and practical experience with containers and orchestration technologies, specifically OpenShift . Demonstrated ability to architect, develop, and deploy highly performant, large-scale AI/ML systems into production environments. Strong understanding of modern software development principles, clean code practices, data structures, algorithms, and distributed systems. Proficiency with Relational (preferably, PostgreSQL) and Vector (preferably, pgvector) databases. Preferred Qualifications (Bonus Points): Proficiency in additional programming languages such as Java, JavaScript/TypeScript, or Golang. Experience with specific frameworks like Spring (AI, Boot), N8N, or Flask. Familiarity with messaging and integration platforms such as Kafka or JMS/MQ. Experience with UI development using modern frameworks like React JS or StreamLit for interactive AI applications. Practical experience in model risk management, developing AI guardrails, and establishing end-user adoption pathways for Generative AI solutions. A proven track record of contributing to open-source projects or publishing relevant research in AI/ML. Why You'll Love Working Here: Unprecedented Impact & Visibility: Contribute to critical, high-visibility projects that are transforming a global enterprise, working on firm-wide initiatives that directly influence our operational future. Cutting-Edge Technology: Work with the latest Generative AI models, agentic frameworks, and cloud-native technologies, enhanced by access to AI-assisted development tools like Devin and Copilot . Growth & Development: A culture of continuous learning, mentorship, and opportunities to lead and innovate. Benefit from extensive learning resources including Udemy for Business and Pluralsight . Collaborative Environment: Join a highly skilled, passionate team that values collaboration, intellectual curiosity, and shared success. Flexible Work Environment: Embrace a hybrid working model, balancing productive in-office collaboration (3 days) with the flexibility of working from home (up to 2 days). Global Scale: Build solutions that operate at a massive scale, impacting users and operations worldwide.Join us to build the future of intelligent enterprise solutions!
About Edra Edra is solving one of the hardest problems in enterprise AI: AI models are generic but company processes are specific. We build AI agents that learn how processes actually run, and then run their operations. We're a Series A startup, backed by Sequoia and other leading VC firms, and we're growing our team in New York and London. We're a deeply technical team of engineers, AI researchers, and strategists with a high bar for talent and a shared belief that exceptional people are the foundation of everything great we'll build. The Role We're looking for Backend Engineers who care deeply about the craft of building software: strong typing, thoughtful API design, robust data modeling, and systems that are a pleasure for other engineers to work with. You won't be building AI models, you'll be building everything around them: the platform, workflows, interfaces, integrations, and observability that make our AI useful in the real world. As an early engineer at Edra, you'll shape not just the product but the engineering culture, tooling choices, and technical foundations the company is built on. We work deliberately and deeply. There's no separation between "building it" and "shipping it" you'll go from whiteboard to production and own the outcome. We'd rather build something thoughtfully than ship something fragile, and we treat velocity and quality as complementary, not competing. What You'll Do Design and build platform systems in Python (Fast API), from API contracts to database schema and infrastructure Build and maintain connectors, integrations, and data pipelines that connect our platform to external systems Build internal libraries, tooling, and interfaces that make the rest of the engineering team more productive Own your work fully: gather context, manage dependencies, and drive tasks to completion without a product manager handing you tickets Wear multiple hats across the stack-you might design a schema in the morning, build the API layer in the afternoon, and debug a deployment issue before end of day Participate in weekly product meetings, understand how customers and forward deployed engineers use what you build, and shape what gets built next Collaborate daily with a small, high-caliber team of engineers and AI specialists Have direct influence on technical direction: choose tools, set patterns, and establish conventions the team will build on for years What We're Looking For 3+ years of experience in software engineering (but a computer science degree is not necessarily required) A love of writing Python and/or TypeScript to a genuinely high standard-well-modeled, well-typed, and well-documented. Strong typing feels like a superpower, not a chore Experience building libraries, SDKs, or internal tooling that made other developers' lives easier (and you've enjoyed it) You light up when designing a clean database schema and take real pride in getting data models right You're at your best when you own a problem end to end - comfortable with ambiguity and energized by turning a vague problem into a well-scoped solution You're drawn to building foundational systems from scratch - greenfield work where your decisions compound over time excites you Don't meet all of the above? We'd still love to hear from you. We're looking for exceptional people with unique skills and interests, and we know that great people have different backgrounds and skillsets. If your primary interest is building agentic systems, working with LLMs, or doing applied ML, check out our AI Engineering role-it might be a better fit. Learn More About Edra Watch our Series A announcement video Read our blog post from our launch Learn more about what we're building A Few Details Edra is an equal opportunity employer and we encourage applications from individuals of all backgrounds. Edra does not discriminate on the basis of race, color, religion, sex, national origin, age, disability, genetic information, marital status, sexual orientation, gender identity, veteran status, or any other legally protected characteristic.
24/07/2026
Full time
About Edra Edra is solving one of the hardest problems in enterprise AI: AI models are generic but company processes are specific. We build AI agents that learn how processes actually run, and then run their operations. We're a Series A startup, backed by Sequoia and other leading VC firms, and we're growing our team in New York and London. We're a deeply technical team of engineers, AI researchers, and strategists with a high bar for talent and a shared belief that exceptional people are the foundation of everything great we'll build. The Role We're looking for Backend Engineers who care deeply about the craft of building software: strong typing, thoughtful API design, robust data modeling, and systems that are a pleasure for other engineers to work with. You won't be building AI models, you'll be building everything around them: the platform, workflows, interfaces, integrations, and observability that make our AI useful in the real world. As an early engineer at Edra, you'll shape not just the product but the engineering culture, tooling choices, and technical foundations the company is built on. We work deliberately and deeply. There's no separation between "building it" and "shipping it" you'll go from whiteboard to production and own the outcome. We'd rather build something thoughtfully than ship something fragile, and we treat velocity and quality as complementary, not competing. What You'll Do Design and build platform systems in Python (Fast API), from API contracts to database schema and infrastructure Build and maintain connectors, integrations, and data pipelines that connect our platform to external systems Build internal libraries, tooling, and interfaces that make the rest of the engineering team more productive Own your work fully: gather context, manage dependencies, and drive tasks to completion without a product manager handing you tickets Wear multiple hats across the stack-you might design a schema in the morning, build the API layer in the afternoon, and debug a deployment issue before end of day Participate in weekly product meetings, understand how customers and forward deployed engineers use what you build, and shape what gets built next Collaborate daily with a small, high-caliber team of engineers and AI specialists Have direct influence on technical direction: choose tools, set patterns, and establish conventions the team will build on for years What We're Looking For 3+ years of experience in software engineering (but a computer science degree is not necessarily required) A love of writing Python and/or TypeScript to a genuinely high standard-well-modeled, well-typed, and well-documented. Strong typing feels like a superpower, not a chore Experience building libraries, SDKs, or internal tooling that made other developers' lives easier (and you've enjoyed it) You light up when designing a clean database schema and take real pride in getting data models right You're at your best when you own a problem end to end - comfortable with ambiguity and energized by turning a vague problem into a well-scoped solution You're drawn to building foundational systems from scratch - greenfield work where your decisions compound over time excites you Don't meet all of the above? We'd still love to hear from you. We're looking for exceptional people with unique skills and interests, and we know that great people have different backgrounds and skillsets. If your primary interest is building agentic systems, working with LLMs, or doing applied ML, check out our AI Engineering role-it might be a better fit. Learn More About Edra Watch our Series A announcement video Read our blog post from our launch Learn more about what we're building A Few Details Edra is an equal opportunity employer and we encourage applications from individuals of all backgrounds. Edra does not discriminate on the basis of race, color, religion, sex, national origin, age, disability, genetic information, marital status, sexual orientation, gender identity, veteran status, or any other legally protected characteristic.
