Our purpose is taking care of life's essentials, but we're also big on making a difference, not just because we should but because we care. AMP8, our next five-year regulatory period, will see us launch our biggest and most complex investment programme of almost £13bn, of which £6bn will be delivered through our capital programme. This is more than double the size of the AMP7 capital programme and is an opportunity to drive real change. As part of that transformation, we're building new capabilities that will help us deliver smarter, faster and more effectively than ever before. One of the boldest is our Capital Delivery AI Transformation Team - a high-profile team created to help unlock major value across AMP 8 and AMP 9, with an ambition to deliver around £0.5bn of value across the programme. This team exists to challenge how things have always been done. It brings together agile thinking, emerging technology and practical delivery to create solutions that remove waste, improve speed and unlock better outcomes across capital delivery. Within that team, Generative AI is playing a critical role in how we reshape delivery - helping us automate repetitive tasks, improve access to knowledge, support better decision-making and create new ways of working across the gated capital process. That's where this role comes in. As our GenAI Lead, you'll help shape how copilots, intelligent assistants, retrieval-based chatbots and agentic workflows are designed, built and deployed across Capital Delivery. This is your opportunity to lead the technical roadmap, define the standards, and make sure our GenAI solutions are secure, scalable, adopted and genuinely valuable. It could be one of the biggest challenges of your career. If you want to do more because you care, we'd love to talk to you. We are looking for a GenAI Lead to join our Capital Delivery AI Transformation Team, helping embed Generative AI into the future of delivery. EVERYTHING YOU NEED TO KNOW Are you excited by the practical application of Generative AI? Do you enjoy turning complex business challenges into secure, scalable technical solutions? Are you someone who can combine deep technical expertise with the ability to bring people with you? As our GenAI Lead, you'll be at the centre of how Generative AI is embedded into capital workflows. You'll lead the design, build and deployment of GenAI solutions including copilots agents and retrieval-based chatbots , helping accelerate Severn Trent's gated capital delivery process and supporting the wider transformation agenda. This role will own the Generative AI technical roadmap, ensuring our direction is aligned to the priorities of the AI Transformation Team and the wider business. You'll define the reference architecture, reusable components, engineering patterns and quality standards that make our GenAI capability both robust and repeatable. Within this role you will: Be a key stakeholder in shaping and continuously evolving the Generative AI technical roadmap, aligned to the team's pods and wider AI portfolio. Define the reference architecture, standards and reusable patterns used across the team, including prompt design, RAG pipelines, evaluation frameworks and guardrails. Make pragmatic build/buy and model-selection decisions, balancing performance, cost, scalability, security and maintainability. Lead the hands on design and build of GenAI products, including copilots, agentic workflows and retrieval based chatbots. Support the movement of prototypes into production through effective CI/CD, LLMOps, monitoring, testing and evaluation. Embed responsible AI, data protection and human in the loop controls into every solution from the start. Establish clear quality, evaluation and assurance standards, ensuring outputs are accurate, safe, explainable and fit for purpose. Work closely with engineers, digital teams and business stakeholders to translate real delivery challenges into practical AI enabled solutions. Technically lead, coach and mentor Automation Engineers and Digital Engineers, helping grow GenAI capability across the team and wider business. Define and track the value and benefits of GenAI deployment against agreed baselines, evidencing adoption, time savings and business impact. Help build confidence in GenAI across Capital Delivery, promoting approaches that are pragmatic, secure and grounded in operational reality. WHAT YOU'LL BRING TO THE ROLE Of course, it's important that we attract the right skill sets, and those with the right experience, but we value character, positivity and a caring attitude in equal weight. We want people who show up and roll their sleeves up. Restless spirits who are ready to be part of something bigger, who care, who really care because when you really care, you'll go above and beyond. When you really care you don't just talk about it, you do more. A degree in Computer Science, Software Engineering, AI Engineering or a related discipline, or equivalent professional experience. Strong understanding of Generative AI / LLM techniques, including RAG, agents, prompt engineering and evaluation. Knowledge of responsible AI, secure development and data protection practices. Demonstrable experience building and deploying production grade LLM / GenAI applications. Strong proficiency in Python and modern AI frameworks such as LangChain, LlamaIndex, vector databases, Azure OpenAI or equivalent. Experience deploying solutions into cloud environments such as Azure or AWS, using CI/CD and MLOps / LLMOps practices. A track record of technical leadership, coaching and mentoring engineers. The ability to translate complex business challenges into practical AI solutions and explain those solutions clearly to non-technical audiences. A delivery focused mindset, with the ability to balance speed, quality, governance and real business value. And it would be great if you also had: A relevant cloud or AI certification such as Azure AI Engineer. Familiarity with NIST or secure by design frameworks. Experience in engineering, construction, utilities or other capital intensive sectors. Familiarity with the Microsoft ecosystem, including Copilot, Power Platform and Fabric. Experience with the Anthropic ecosystem / ClaudeCode. We welcome people from all walks of life and celebrate individuality as we know diverse minds, experiences and backgrounds help us to learn and better serve our communities. We employ thousands of people from across our community who really care about what they do. Because that is how we do what we do. And when it comes to inclusion, we're making sure we keep up the progress with our wonderful working groups - LGBTQ+, Women in Operations & STEM, Disability and Ethnicity, who help us do just that. Working here isn't just a job. You can build a career at Severn Trent. We'll reward you for it, too. We have a range of benefits that recognise great work, and award winning training to help you reach your potential. And we'll also help you play your part in looking after the environment and the communities where we live. With that in mind, here are just some of our favourite perks that you'll get being part of the Severn Trent family: 28 days holiday + bank holidays (and the ability to buy/sell up to 5 days per year) Annual bonus scheme (of up to £2,250, which is subject to eligibility) Leading pension scheme - we will double your contribution (up to 15% when you contribute 7.5%) Sharesave - the chance to buy Severn Trent Plc shares at a discounted rate Dedicated training and development with our Academy Electric vehicle scheme and retail offers Family friendly policies Two paid volunteering days per year WHAT'S NEXT? We can't wait to hear from you. Before you apply, you'll need an updated copy of your CV and about five minutes to spare. And if your curiosity has peaked and you're wanting to find out even more, search on social media. Ps. we'll always let you know the outcome of your application after the closing date - so keep an eye on your phone and emails!
27/06/2026
Full time
Our purpose is taking care of life's essentials, but we're also big on making a difference, not just because we should but because we care. AMP8, our next five-year regulatory period, will see us launch our biggest and most complex investment programme of almost £13bn, of which £6bn will be delivered through our capital programme. This is more than double the size of the AMP7 capital programme and is an opportunity to drive real change. As part of that transformation, we're building new capabilities that will help us deliver smarter, faster and more effectively than ever before. One of the boldest is our Capital Delivery AI Transformation Team - a high-profile team created to help unlock major value across AMP 8 and AMP 9, with an ambition to deliver around £0.5bn of value across the programme. This team exists to challenge how things have always been done. It brings together agile thinking, emerging technology and practical delivery to create solutions that remove waste, improve speed and unlock better outcomes across capital delivery. Within that team, Generative AI is playing a critical role in how we reshape delivery - helping us automate repetitive tasks, improve access to knowledge, support better decision-making and create new ways of working across the gated capital process. That's where this role comes in. As our GenAI Lead, you'll help shape how copilots, intelligent assistants, retrieval-based chatbots and agentic workflows are designed, built and deployed across Capital Delivery. This is your opportunity to lead the technical roadmap, define the standards, and make sure our GenAI solutions are secure, scalable, adopted and genuinely valuable. It could be one of the biggest challenges of your career. If you want to do more because you care, we'd love to talk to you. We are looking for a GenAI Lead to join our Capital Delivery AI Transformation Team, helping embed Generative AI into the future of delivery. EVERYTHING YOU NEED TO KNOW Are you excited by the practical application of Generative AI? Do you enjoy turning complex business challenges into secure, scalable technical solutions? Are you someone who can combine deep technical expertise with the ability to bring people with you? As our GenAI Lead, you'll be at the centre of how Generative AI is embedded into capital workflows. You'll lead the design, build and deployment of GenAI solutions including copilots agents and retrieval-based chatbots , helping accelerate Severn Trent's gated capital delivery process and supporting the wider transformation agenda. This role will own the Generative AI technical roadmap, ensuring our direction is aligned to the priorities of the AI Transformation Team and the wider business. You'll define the reference architecture, reusable components, engineering patterns and quality standards that make our GenAI capability both robust and repeatable. Within this role you will: Be a key stakeholder in shaping and continuously evolving the Generative AI technical roadmap, aligned to the team's pods and wider AI portfolio. Define the reference architecture, standards and reusable patterns used across the team, including prompt design, RAG pipelines, evaluation frameworks and guardrails. Make pragmatic build/buy and model-selection decisions, balancing performance, cost, scalability, security and maintainability. Lead the hands on design and build of GenAI products, including copilots, agentic workflows and retrieval based chatbots. Support the movement of prototypes into production through effective CI/CD, LLMOps, monitoring, testing and evaluation. Embed responsible AI, data protection and human in the loop controls into every solution from the start. Establish clear quality, evaluation and assurance standards, ensuring outputs are accurate, safe, explainable and fit for purpose. Work closely with engineers, digital teams and business stakeholders to translate real delivery challenges into practical AI enabled solutions. Technically lead, coach and mentor Automation Engineers and Digital Engineers, helping grow GenAI capability across the team and wider business. Define and track the value and benefits of GenAI deployment against agreed baselines, evidencing adoption, time savings and business impact. Help build confidence in GenAI across Capital Delivery, promoting approaches that are pragmatic, secure and grounded in operational reality. WHAT YOU'LL BRING TO THE ROLE Of course, it's important that we attract the right skill sets, and those with the right experience, but we value character, positivity and a caring attitude in equal weight. We want people who show up and roll their sleeves up. Restless spirits who are ready to be part of something bigger, who care, who really care because when you really care, you'll go above and beyond. When you really care you don't just talk about it, you do more. A degree in Computer Science, Software Engineering, AI Engineering or a related discipline, or equivalent professional experience. Strong understanding of Generative AI / LLM techniques, including RAG, agents, prompt engineering and evaluation. Knowledge of responsible AI, secure development and data protection practices. Demonstrable experience building and deploying production grade LLM / GenAI applications. Strong proficiency in Python and modern AI frameworks such as LangChain, LlamaIndex, vector databases, Azure OpenAI or equivalent. Experience deploying solutions into cloud environments such as Azure or AWS, using CI/CD and MLOps / LLMOps practices. A track record of technical leadership, coaching and mentoring engineers. The ability to translate complex business challenges into practical AI solutions and explain those solutions clearly to non-technical audiences. A delivery focused mindset, with the ability to balance speed, quality, governance and real business value. And it would be great if you also had: A relevant cloud or AI certification such as Azure AI Engineer. Familiarity with NIST or secure by design frameworks. Experience in engineering, construction, utilities or other capital intensive sectors. Familiarity with the Microsoft ecosystem, including Copilot, Power Platform and Fabric. Experience with the Anthropic ecosystem / ClaudeCode. We welcome people from all walks of life and celebrate individuality as we know diverse minds, experiences and backgrounds help us to learn and better serve our communities. We employ thousands of people from across our community who really care about what they do. Because that is how we do what we do. And when it comes to inclusion, we're making sure we keep up the progress with our wonderful working groups - LGBTQ+, Women in Operations & STEM, Disability and Ethnicity, who help us do just that. Working here isn't just a job. You can build a career at Severn Trent. We'll reward you for it, too. We have a range of benefits that recognise great work, and award winning training to help you reach your potential. And we'll also help you play your part in looking after the environment and the communities where we live. With that in mind, here are just some of our favourite perks that you'll get being part of the Severn Trent family: 28 days holiday + bank holidays (and the ability to buy/sell up to 5 days per year) Annual bonus scheme (of up to £2,250, which is subject to eligibility) Leading pension scheme - we will double your contribution (up to 15% when you contribute 7.5%) Sharesave - the chance to buy Severn Trent Plc shares at a discounted rate Dedicated training and development with our Academy Electric vehicle scheme and retail offers Family friendly policies Two paid volunteering days per year WHAT'S NEXT? We can't wait to hear from you. Before you apply, you'll need an updated copy of your CV and about five minutes to spare. And if your curiosity has peaked and you're wanting to find out even more, search on social media. Ps. we'll always let you know the outcome of your application after the closing date - so keep an eye on your phone and emails!
The AI Engineer designs, builds and operates scalable, secure AI solutions for JCDecaux UK, with a focus on Copilot implementations and agentic AI that augment users and automate complex workflows. The role converts business and data requirements into production grade AI assistants, copilots and intelligent agents embedded into products, processes and decision making. Working closely with technology and business teams, the AI Engineer oversees solutions from experimentation through to deployment, optimisation and support, ensuring they integrate with JCDecaux UK's digital, data and technology landscape. The role supports JCDecaux UK's vision and mission by using advanced AI to pioneer real world communications and enhance client and consumer understanding. Reports to: Chief Innovation and Technology Officer What you'll be doing Design and implement AI copilots and agentic AI solutions that assist users, automate multi step tasks and orchestrate calls to internal tools and systems. Translate business use cases into Copilot scenarios, prompt flows, connectors and agent behaviours, defining secure, scalable solution architectures. Build and maintain AI components (e.g. RAG, classification, recommendation, summarisation) using Python and modern ML/LLM frameworks. Implement end to end MLOps pipelines for development, testing, deployment and monitoring of Copilot and AI solutions, and deploy them into production environments (e.g. Microsoft 365 Copilot, Azure, internal apps). Integrate AI agents with enterprise systems (e.g. CRM, ERP, scheduling, inventory, data platforms) via APIs and microservices. Collaborate with data engineers to design data pipelines, retrieval layers (vector stores, search indices) and large scale processing using big data frameworks. Implement monitoring, logging and analytics to track usage, performance, quality and user satisfaction, and lead optimisation to address issues such as drift, hallucinations and latency. Contribute to AI engineering standards, guardrails and best practices, and support incident investigation and resolution with Service Delivery. Ensure solutions comply with security, privacy, compliance and ethical AI requirements, including access controls, data protection and risk assessments. Share knowledge and mentor colleagues to build AI literacy and capability across IT and the wider business. A little bit about you Degree in Computer Science, Data Science, Software Engineering, Mathematics, Engineering or a closely related field. Previous experience in AI, data science, ML engineering or advanced analytics. Hands on experience designing, building and deploying Copilot and/or agentic AI solutions (e.g. Microsoft 365 Copilot extensions, Azure OpenAI based copilots, custom AI assistants/agents). Strong proficiency in Python for AI/ML development, including use of common ML and data libraries (e.g. TensorFlow/PyTorch, scikit learn, pandas, NumPy). Proven experience integrating AI services with enterprise systems via APIs and event driven architectures. Practical experience with LLMs, prompt engineering, RAG and tools/plugins for agents and copilots. Familiarity with cloud platforms (ideally Azure) and AI services (e.g. Azure OpenAI, Azure Machine Learning, or equivalents). Experience working in agile, cross functional delivery teams. Postgraduate study or certifications in AI, machine learning or data science. Cloud certifications (e.g. Azure, GCP, AWS) and relevant AI/ML credentials. Experience with big data and distributed computing (e.g. Spark, Databricks, Hadoop or cloud native alternatives). Experience with containerisation and DevOps/MLOps tools (e.g. Docker, Kubernetes, Git, CI/CD, MLflow, Airflow). Strong experience with data engineering concepts (ETL/ELT, data integration, warehousing, vector databases/search). We are committed to equal employment opportunities regardless of race, colour, ancestry, religion, national origin, sexual orientation, age, citizenship, marital status, disability or gender identity.
27/06/2026
Full time
The AI Engineer designs, builds and operates scalable, secure AI solutions for JCDecaux UK, with a focus on Copilot implementations and agentic AI that augment users and automate complex workflows. The role converts business and data requirements into production grade AI assistants, copilots and intelligent agents embedded into products, processes and decision making. Working closely with technology and business teams, the AI Engineer oversees solutions from experimentation through to deployment, optimisation and support, ensuring they integrate with JCDecaux UK's digital, data and technology landscape. The role supports JCDecaux UK's vision and mission by using advanced AI to pioneer real world communications and enhance client and consumer understanding. Reports to: Chief Innovation and Technology Officer What you'll be doing Design and implement AI copilots and agentic AI solutions that assist users, automate multi step tasks and orchestrate calls to internal tools and systems. Translate business use cases into Copilot scenarios, prompt flows, connectors and agent behaviours, defining secure, scalable solution architectures. Build and maintain AI components (e.g. RAG, classification, recommendation, summarisation) using Python and modern ML/LLM frameworks. Implement end to end MLOps pipelines for development, testing, deployment and monitoring of Copilot and AI solutions, and deploy them into production environments (e.g. Microsoft 365 Copilot, Azure, internal apps). Integrate AI agents with enterprise systems (e.g. CRM, ERP, scheduling, inventory, data platforms) via APIs and microservices. Collaborate with data engineers to design data pipelines, retrieval layers (vector stores, search indices) and large scale processing using big data frameworks. Implement monitoring, logging and analytics to track usage, performance, quality and user satisfaction, and lead optimisation to address issues such as drift, hallucinations and latency. Contribute to AI engineering standards, guardrails and best practices, and support incident investigation and resolution with Service Delivery. Ensure solutions comply with security, privacy, compliance and ethical AI requirements, including access controls, data protection and risk assessments. Share knowledge and mentor colleagues to build AI literacy and capability across IT and the wider business. A little bit about you Degree in Computer Science, Data Science, Software Engineering, Mathematics, Engineering or a closely related field. Previous experience in AI, data science, ML engineering or advanced analytics. Hands on experience designing, building and deploying Copilot and/or agentic AI solutions (e.g. Microsoft 365 Copilot extensions, Azure OpenAI based copilots, custom AI assistants/agents). Strong proficiency in Python for AI/ML development, including use of common ML and data libraries (e.g. TensorFlow/PyTorch, scikit learn, pandas, NumPy). Proven experience integrating AI services with enterprise systems via APIs and event driven architectures. Practical experience with LLMs, prompt engineering, RAG and tools/plugins for agents and copilots. Familiarity with cloud platforms (ideally Azure) and AI services (e.g. Azure OpenAI, Azure Machine Learning, or equivalents). Experience working in agile, cross functional delivery teams. Postgraduate study or certifications in AI, machine learning or data science. Cloud certifications (e.g. Azure, GCP, AWS) and relevant AI/ML credentials. Experience with big data and distributed computing (e.g. Spark, Databricks, Hadoop or cloud native alternatives). Experience with containerisation and DevOps/MLOps tools (e.g. Docker, Kubernetes, Git, CI/CD, MLflow, Airflow). Strong experience with data engineering concepts (ETL/ELT, data integration, warehousing, vector databases/search). We are committed to equal employment opportunities regardless of race, colour, ancestry, religion, national origin, sexual orientation, age, citizenship, marital status, disability or gender identity.
Capital One is seeking a Staff Software Engineer specialized in Machine Learning to drive the technical strategy across multiple teams in London. You will spearhead ML/AI initiatives and collaborate with various teams to enhance company capabilities through innovative AI solutions. We offer a hybrid work model, allowing flexibility to work from home and our London office. Enjoy numerous benefits, including a pension scheme and private medical insurance, as well as a commitment to your career development.
27/06/2026
Full time
Capital One is seeking a Staff Software Engineer specialized in Machine Learning to drive the technical strategy across multiple teams in London. You will spearhead ML/AI initiatives and collaborate with various teams to enhance company capabilities through innovative AI solutions. We offer a hybrid work model, allowing flexibility to work from home and our London office. Enjoy numerous benefits, including a pension scheme and private medical insurance, as well as a commitment to your career development.
Multiverse Computing Multiverse Computing is a fast growing deep tech company founded in 2019 and recognized by CB Insights as one of the 100 most promising AI companies globally. We are the largest quantum software company in the EU, with 250+ employees worldwide building advanced AI and quantum solutions that help enterprises tackle complex, high impact challenges across industries such as finance, energy, manufacturing, telecom, and industrials. Our mission is to enable organizations to gain a meaningful competitive edge through cutting edge AI and quantum technologies. Why join us? We are a European deep tech leader in quantum and AI, backed by major global strategic investors and strong EU support. Our groundbreaking technology is already transforming how AI is deployed worldwide - compressing large language models by up to 95% without losing accuracy and cutting inference costs by 50-80%. Joining us means working on cutting edge solutions that make AI faster, greener, and more accessible - and being part of a company often described as a "quantum AI unicorn in the making." This opportunity is to work in our offices in London, UK. We are looking for a talented Solutions Architect to join our pre sales team and bridge the gap between our technology and our customers' needs, crafting innovative, scalable, and robust AI powered solutions. Key requirements Previous experience in a technical partner pre sales or consulting role with a heavy emphasis on partner and customer facing interactions (i.e. Solutions Architect, Sales Engineer, Implementation Consultant) Excellent communication and presentation skills, able to interface effectively with technical and non technical stakeholders; experience writing technical proposals or responding to RFPs/tenders; experience running hands on product demos independently. Strong knowledge of cloud platforms (AWS, Azure, GCP) and AI/ML services (e.g., SageMaker, Vertex AI, AzureML), including sovereign, on premise, and hybrid deployment models. Familiarity with MLOps tools and practices: CI/CD, monitoring, and orchestration frameworks (e.g., Kubeflow, Flyte, MLflow); proficiency with Docker and Kubernetes for AI workload containerization. Understanding of LLM inference stacks (vLLM, llama.cpp, OpenVINO) and model delivery formats (ONNX, .safetensors, Hugging Face model hub). Experience sizing GPU infrastructure for LLM inference or training workloads (memory, throughput, hardware tiers from A10 to H200). Experience benchmarking and evaluating LLM performance (accuracy, latency, throughput). Hands on coding skills in Python, SQL, and familiarity with ML libraries and frameworks (PyTorch, TensorFlow, Hugging Face). Bachelor's or master's degree in Computer Science, Data Science, Engineering, or related field. Must be available to travel as needed for meetings, conferences, and project requirements. Languages: English Preferred Qualifications Experience with Computer Vision models, Speech models, Vision Language models, and other modalities. Experience with AI model optimization, quantization, or deployment to edge devices. Hands on experience designing RAG pipelines and/or multi agent systems. Experience designing data architectures (batch & streaming) and working with big data technologies. Knowledge of data privacy and ethical considerations in AI, including GDPR compliance and familiarity with the EU AI Act. Location Applicants must have legal authorization to work in the country where the position is based. Perks & Benefits Equal pay guaranteed. Signing bonus. Relocation package (if applicable). Eligibility for educational budget according to internal policy. Hybrid opportunity. Flexible working hours. Language classes and discounted lunch options Working in a high paced environment, working on cutting edge technologies. Career plan. Opportunity to learn and teach. As an equal opportunity employer, Multiverse Computing is committed to building an inclusive workplace. The company welcomes people from all different backgrounds, including age, citizenship, ethnic and racial origins, gender identities, individuals with disabilities, marital status, religions and ideologies, and sexual orientations to apply.
27/06/2026
Full time
Multiverse Computing Multiverse Computing is a fast growing deep tech company founded in 2019 and recognized by CB Insights as one of the 100 most promising AI companies globally. We are the largest quantum software company in the EU, with 250+ employees worldwide building advanced AI and quantum solutions that help enterprises tackle complex, high impact challenges across industries such as finance, energy, manufacturing, telecom, and industrials. Our mission is to enable organizations to gain a meaningful competitive edge through cutting edge AI and quantum technologies. Why join us? We are a European deep tech leader in quantum and AI, backed by major global strategic investors and strong EU support. Our groundbreaking technology is already transforming how AI is deployed worldwide - compressing large language models by up to 95% without losing accuracy and cutting inference costs by 50-80%. Joining us means working on cutting edge solutions that make AI faster, greener, and more accessible - and being part of a company often described as a "quantum AI unicorn in the making." This opportunity is to work in our offices in London, UK. We are looking for a talented Solutions Architect to join our pre sales team and bridge the gap between our technology and our customers' needs, crafting innovative, scalable, and robust AI powered solutions. Key requirements Previous experience in a technical partner pre sales or consulting role with a heavy emphasis on partner and customer facing interactions (i.e. Solutions Architect, Sales Engineer, Implementation Consultant) Excellent communication and presentation skills, able to interface effectively with technical and non technical stakeholders; experience writing technical proposals or responding to RFPs/tenders; experience running hands on product demos independently. Strong knowledge of cloud platforms (AWS, Azure, GCP) and AI/ML services (e.g., SageMaker, Vertex AI, AzureML), including sovereign, on premise, and hybrid deployment models. Familiarity with MLOps tools and practices: CI/CD, monitoring, and orchestration frameworks (e.g., Kubeflow, Flyte, MLflow); proficiency with Docker and Kubernetes for AI workload containerization. Understanding of LLM inference stacks (vLLM, llama.cpp, OpenVINO) and model delivery formats (ONNX, .safetensors, Hugging Face model hub). Experience sizing GPU infrastructure for LLM inference or training workloads (memory, throughput, hardware tiers from A10 to H200). Experience benchmarking and evaluating LLM performance (accuracy, latency, throughput). Hands on coding skills in Python, SQL, and familiarity with ML libraries and frameworks (PyTorch, TensorFlow, Hugging Face). Bachelor's or master's degree in Computer Science, Data Science, Engineering, or related field. Must be available to travel as needed for meetings, conferences, and project requirements. Languages: English Preferred Qualifications Experience with Computer Vision models, Speech models, Vision Language models, and other modalities. Experience with AI model optimization, quantization, or deployment to edge devices. Hands on experience designing RAG pipelines and/or multi agent systems. Experience designing data architectures (batch & streaming) and working with big data technologies. Knowledge of data privacy and ethical considerations in AI, including GDPR compliance and familiarity with the EU AI Act. Location Applicants must have legal authorization to work in the country where the position is based. Perks & Benefits Equal pay guaranteed. Signing bonus. Relocation package (if applicable). Eligibility for educational budget according to internal policy. Hybrid opportunity. Flexible working hours. Language classes and discounted lunch options Working in a high paced environment, working on cutting edge technologies. Career plan. Opportunity to learn and teach. As an equal opportunity employer, Multiverse Computing is committed to building an inclusive workplace. The company welcomes people from all different backgrounds, including age, citizenship, ethnic and racial origins, gender identities, individuals with disabilities, marital status, religions and ideologies, and sexual orientations to apply.
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.
27/06/2026
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.
Multiverse Computing Multiverse Computing is a fast growing deep tech company founded in 2019 and recognized by CB Insights as one of the 100 most promising AI companies globally. We are the largest quantum software company in the EU, with 250+ employees worldwide building advanced AI and quantum solutions that help enterprises tackle complex, high impact challenges across industries such as finance, energy, manufacturing, telecom, and industrials. Our mission is to enable organizations to gain a meaningful competitive edge through cutting edge AI and quantum technologies. Why join us? We are a European deep tech leader in quantum and AI, backed by major global strategic investors and strong EU support. Our groundbreaking technology is already transforming how AI is deployed worldwide - compressing large language models by up to 95% without losing accuracy and cutting inference costs by 50-80%. Joining us means working on cutting edge solutions that make AI faster, greener, and more accessible - and being part of a company often described as a "quantum AI unicorn in the making." This opportunity is to work in our offices in London, UK. We are looking for a talented Solutions Architect to join our pre sales team and bridge the gap between our technology and our customers' needs, crafting innovative, scalable, and robust AI powered solutions. Key requirements Previous experience in a technical partner pre sales or consulting role with a heavy emphasis on partner and customer facing interactions (i.e. Solutions Architect, Sales Engineer, Implementation Consultant) Excellent communication and presentation skills, able to interface effectively with technical and non technical stakeholders; experience writing technical proposals or responding to RFPs/tenders; experience running hands on product demos independently. Strong knowledge of cloud platforms (AWS, Azure, GCP) and AI/ML services (e.g., SageMaker, Vertex AI, AzureML), including sovereign, on premise, and hybrid deployment models. Familiarity with MLOps tools and practices: CI/CD, monitoring, and orchestration frameworks (e.g., Kubeflow, Flyte, MLflow); proficiency with Docker and Kubernetes for AI workload containerization. Understanding of LLM inference stacks (vLLM, llama.cpp, OpenVINO) and model delivery formats (ONNX, .safetensors, Hugging Face model hub). Experience sizing GPU infrastructure for LLM inference or training workloads (memory, throughput, hardware tiers from A10 to H200). Experience benchmarking and evaluating LLM performance (accuracy, latency, throughput). Hands on coding skills in Python, SQL, and familiarity with ML libraries and frameworks (PyTorch, TensorFlow, Hugging Face). Bachelor's or master's degree in Computer Science, Data Science, Engineering, or related field. Must be available to travel as needed for meetings, conferences, and project requirements. Languages: English Preferred Qualifications Experience with Computer Vision models, Speech models, Vision Language models, and other modalities. Experience with AI model optimization, quantization, or deployment to edge devices. Hands on experience designing RAG pipelines and/or multi agent systems. Experience designing data architectures (batch & streaming) and working with big data technologies. Knowledge of data privacy and ethical considerations in AI, including GDPR compliance and familiarity with the EU AI Act. Location Applicants must have legal authorization to work in the country where the position is based. Perks & Benefits Equal pay guaranteed. Signing bonus. Relocation package (if applicable). Eligibility for educational budget according to internal policy. Hybrid opportunity. Flexible working hours. Language classes and discounted lunch options Working in a high paced environment, working on cutting edge technologies. Career plan. Opportunity to learn and teach. As an equal opportunity employer, Multiverse Computing is committed to building an inclusive workplace. The company welcomes people from all different backgrounds, including age, citizenship, ethnic and racial origins, gender identities, individuals with disabilities, marital status, religions and ideologies, and sexual orientations to apply.
27/06/2026
Full time
Multiverse Computing Multiverse Computing is a fast growing deep tech company founded in 2019 and recognized by CB Insights as one of the 100 most promising AI companies globally. We are the largest quantum software company in the EU, with 250+ employees worldwide building advanced AI and quantum solutions that help enterprises tackle complex, high impact challenges across industries such as finance, energy, manufacturing, telecom, and industrials. Our mission is to enable organizations to gain a meaningful competitive edge through cutting edge AI and quantum technologies. Why join us? We are a European deep tech leader in quantum and AI, backed by major global strategic investors and strong EU support. Our groundbreaking technology is already transforming how AI is deployed worldwide - compressing large language models by up to 95% without losing accuracy and cutting inference costs by 50-80%. Joining us means working on cutting edge solutions that make AI faster, greener, and more accessible - and being part of a company often described as a "quantum AI unicorn in the making." This opportunity is to work in our offices in London, UK. We are looking for a talented Solutions Architect to join our pre sales team and bridge the gap between our technology and our customers' needs, crafting innovative, scalable, and robust AI powered solutions. Key requirements Previous experience in a technical partner pre sales or consulting role with a heavy emphasis on partner and customer facing interactions (i.e. Solutions Architect, Sales Engineer, Implementation Consultant) Excellent communication and presentation skills, able to interface effectively with technical and non technical stakeholders; experience writing technical proposals or responding to RFPs/tenders; experience running hands on product demos independently. Strong knowledge of cloud platforms (AWS, Azure, GCP) and AI/ML services (e.g., SageMaker, Vertex AI, AzureML), including sovereign, on premise, and hybrid deployment models. Familiarity with MLOps tools and practices: CI/CD, monitoring, and orchestration frameworks (e.g., Kubeflow, Flyte, MLflow); proficiency with Docker and Kubernetes for AI workload containerization. Understanding of LLM inference stacks (vLLM, llama.cpp, OpenVINO) and model delivery formats (ONNX, .safetensors, Hugging Face model hub). Experience sizing GPU infrastructure for LLM inference or training workloads (memory, throughput, hardware tiers from A10 to H200). Experience benchmarking and evaluating LLM performance (accuracy, latency, throughput). Hands on coding skills in Python, SQL, and familiarity with ML libraries and frameworks (PyTorch, TensorFlow, Hugging Face). Bachelor's or master's degree in Computer Science, Data Science, Engineering, or related field. Must be available to travel as needed for meetings, conferences, and project requirements. Languages: English Preferred Qualifications Experience with Computer Vision models, Speech models, Vision Language models, and other modalities. Experience with AI model optimization, quantization, or deployment to edge devices. Hands on experience designing RAG pipelines and/or multi agent systems. Experience designing data architectures (batch & streaming) and working with big data technologies. Knowledge of data privacy and ethical considerations in AI, including GDPR compliance and familiarity with the EU AI Act. Location Applicants must have legal authorization to work in the country where the position is based. Perks & Benefits Equal pay guaranteed. Signing bonus. Relocation package (if applicable). Eligibility for educational budget according to internal policy. Hybrid opportunity. Flexible working hours. Language classes and discounted lunch options Working in a high paced environment, working on cutting edge technologies. Career plan. Opportunity to learn and teach. As an equal opportunity employer, Multiverse Computing is committed to building an inclusive workplace. The company welcomes people from all different backgrounds, including age, citizenship, ethnic and racial origins, gender identities, individuals with disabilities, marital status, religions and ideologies, and sexual orientations to apply.
About this role White Collar Factory (95009), United Kingdom, London - Staff Software Engineer (Machine Learning). We're on a mission to transform the way we use data and AI to service our customers and drive efficiency across the business. Do you love shaping the technical landscape and driving innovation across the organisation? Are you passionate about solving complex ML and AI challenges and supporting multiple teams toward a shared technical vision? At Capital One, you'll be part of a community of technical leaders who drive engineering excellence, foster innovation, and deliver impactful ML/AI and Gen AI solutions that meet real customer needs. What You'll Do Own and drive the ML/AI technical strategy for UK use cases, spanning multiple teams and influencing the overall technical direction for AI adoption. Lead and coordinate ML engineering efforts across multiple teams, ensuring alignment with broader business objectives, enterprise platform capabilities, and technology strategy. Provide technical consultancy to teams delivering AI use cases, guiding architectural decisions, solution design, and effective use of enterprise ML/AI platforms and capabilities. Proactively identify emerging ML/AI patterns, define and evangelise best practices, and establish reusable approaches that enhance delivery of AI use cases across the business. Drive MLOps standards and practices across teams, including CI/CD for models, automated testing, monitoring, and deployment pipelines. Collaborate with enterprise platform and data science teams, contributing to platform capabilities where appropriate and partnering on use case delivery. Build and maintain strong relationships with key stakeholders, including senior leadership, product owners, data science teams, and enterprise platform partners. Represent Capital One in external ML/AI technical forums, contributing to industry discussions. Develop and advocate for strategies to proactively manage technical debt across ML/AI systems. Actively mentor and develop engineers, fostering a culture of continuous learning. What We're Looking For Deep expertise in Python and ML engineering. Deep expertise in ML/AI systems design, MLOps, and cloud native architectures. Track record of leading ML/AI technical initiatives across multiple teams. Strong experience with cloud platforms (AWS, Azure, GCP). Experience with ML frameworks (PyTorch, TensorFlow, scikit learn) and Gen AI/Agentic frameworks (LangGraph, LangChain, VectorDBs, RAG). Understanding of responsible AI practices, including guardrails, hallucination mitigation, and output quality management for AI systems. Experience designing and scaling low latency, customer facing ML/AI architectures. Proven experience setting a multi team ML/AI technical vision and strategy. Strong track record of technical leadership and influence without authority. Experience driving ML engineering standards and best practices across organisations. Deep understanding of the full ML/AI development lifecycle, including model serving, data pipelines, and Gen AI systems. Experience leveraging enterprise platforms to deliver business use cases at scale. Experience steering Communities of Practice or technical forums. Strong business acumen and ability to translate ML/AI concepts for various audiences. Where and How You'll Work This is a permanent position based in our London office. We have a hybrid working model which gives you flexibility to work from our office and from home. You will be based in our London office 3 days a week: Tuesday, Wednesday and Thursday. Benefits High performers strong and diverse career progression, investing heavily in developing great people through our Capital One University training programmes and appropriate external providers. Immediate access to core benefits including pension scheme, bonus, generous holiday entitlement and private medical insurance - with flexible benefits available (season ticket loans, cycle to work scheme and enhanced parental leave). Open plan workspaces and accessible facilities designed to inspire and support you. Gym, subsidised restaurant, mindfulness and music rooms at our Nottingham head office (further details can be provided). Equal Employment Opportunity Capital One is committed to diversity in the workplace. If you require a reasonable adjustment, please let us know. All information will be kept confidential and will only be used for the purpose of applying a reasonable adjustment.
27/06/2026
Full time
About this role White Collar Factory (95009), United Kingdom, London - Staff Software Engineer (Machine Learning). We're on a mission to transform the way we use data and AI to service our customers and drive efficiency across the business. Do you love shaping the technical landscape and driving innovation across the organisation? Are you passionate about solving complex ML and AI challenges and supporting multiple teams toward a shared technical vision? At Capital One, you'll be part of a community of technical leaders who drive engineering excellence, foster innovation, and deliver impactful ML/AI and Gen AI solutions that meet real customer needs. What You'll Do Own and drive the ML/AI technical strategy for UK use cases, spanning multiple teams and influencing the overall technical direction for AI adoption. Lead and coordinate ML engineering efforts across multiple teams, ensuring alignment with broader business objectives, enterprise platform capabilities, and technology strategy. Provide technical consultancy to teams delivering AI use cases, guiding architectural decisions, solution design, and effective use of enterprise ML/AI platforms and capabilities. Proactively identify emerging ML/AI patterns, define and evangelise best practices, and establish reusable approaches that enhance delivery of AI use cases across the business. Drive MLOps standards and practices across teams, including CI/CD for models, automated testing, monitoring, and deployment pipelines. Collaborate with enterprise platform and data science teams, contributing to platform capabilities where appropriate and partnering on use case delivery. Build and maintain strong relationships with key stakeholders, including senior leadership, product owners, data science teams, and enterprise platform partners. Represent Capital One in external ML/AI technical forums, contributing to industry discussions. Develop and advocate for strategies to proactively manage technical debt across ML/AI systems. Actively mentor and develop engineers, fostering a culture of continuous learning. What We're Looking For Deep expertise in Python and ML engineering. Deep expertise in ML/AI systems design, MLOps, and cloud native architectures. Track record of leading ML/AI technical initiatives across multiple teams. Strong experience with cloud platforms (AWS, Azure, GCP). Experience with ML frameworks (PyTorch, TensorFlow, scikit learn) and Gen AI/Agentic frameworks (LangGraph, LangChain, VectorDBs, RAG). Understanding of responsible AI practices, including guardrails, hallucination mitigation, and output quality management for AI systems. Experience designing and scaling low latency, customer facing ML/AI architectures. Proven experience setting a multi team ML/AI technical vision and strategy. Strong track record of technical leadership and influence without authority. Experience driving ML engineering standards and best practices across organisations. Deep understanding of the full ML/AI development lifecycle, including model serving, data pipelines, and Gen AI systems. Experience leveraging enterprise platforms to deliver business use cases at scale. Experience steering Communities of Practice or technical forums. Strong business acumen and ability to translate ML/AI concepts for various audiences. Where and How You'll Work This is a permanent position based in our London office. We have a hybrid working model which gives you flexibility to work from our office and from home. You will be based in our London office 3 days a week: Tuesday, Wednesday and Thursday. Benefits High performers strong and diverse career progression, investing heavily in developing great people through our Capital One University training programmes and appropriate external providers. Immediate access to core benefits including pension scheme, bonus, generous holiday entitlement and private medical insurance - with flexible benefits available (season ticket loans, cycle to work scheme and enhanced parental leave). Open plan workspaces and accessible facilities designed to inspire and support you. Gym, subsidised restaurant, mindfulness and music rooms at our Nottingham head office (further details can be provided). Equal Employment Opportunity Capital One is committed to diversity in the workplace. If you require a reasonable adjustment, please let us know. All information will be kept confidential and will only be used for the purpose of applying a reasonable adjustment.
Role Purpose As a Lead Machine Learning Engineer (MLE) at Hiscox, you will shape and scale our Machine Learning Engineering capability and ensure the successful deployment and operation of ML in production. You will lead the MLE sub chapter, line manage Machine Learning Engineers, and partner closely with the Head of Data Science, the Data Science sub chapters and Platform/Group teams to enable scalable, reusable, and well governed ML solutions. You will be accountable for the MLOps platform, ensuring it is reliable, secure, and continuously evolved and for ensuring our business unit ships ML to production in a scalable way that is reusable across value streams, enabling efficient model maintenance, monitoring, and lifecycle management. Combining deep technical expertise with leadership, you will set standards, uplift capability, and enable squads to deliver robust, production grade ML systems. Responsibilities People Leadership: Manage and grow talent; set objectives, conduct performance reviews, and guide career progression for the MLE sub chapter. Foster a strong engineering culture: Promote collaboration, psychological safety, and high standards of quality and reliability. Provide coaching and mentorship: Support technical and professional development of Machine Learning Engineers. Strategic Capability Development: Define and evolve chapter strategy; align sub chapter goals with chapter and organisational objectives. Shape technical direction: Establish standards for ML engineering, deployment patterns, and MLOps. Drive upskilling and cross skilling: Build capability in production ML, platform usage, and software engineering best practices. Technical Enablement & Platform Ownership: Own and evolve the MLOps platform; ensure it is reliable, secure, and scalable. Enable scalable and reusable ML delivery: Ensure ML solutions for the business unit are deployable across value streams and efficient to operate. Lead technical spikes and proof of concepts: De risk architectural decisions and explore new tools and approaches. Governance & Standards: Ensure compliance, security, architecture, and operational standards. Define guardrails for production ML systems covering deployment, monitoring, retraining, and decommissioning in collaboration with Data Science. Collaboration & Influence: Partner closely with the Data Science sub chapters and delivery team to ensure effective handover from experimentation to production. Represent Machine Learning Engineering in strategic forums and advocate for platforms, tooling, and scalable ML practices. Qualifications Bachelor's or Master's in Computer Science, Engineering, or a related quantitative field (or equivalent experience). Experience as a Senior/Lead Machine Learning Engineer delivering production ML systems at scale. Solid understanding of core data science concepts, including supervised and unsupervised learning, feature engineering, and model evaluation. Working knowledge of statistical concepts and model evaluation techniques sufficient to review, validate, and productionise data science work. Proven line management and/or technical mentorship of engineers; building capability and setting standards. Demonstrated ownership of MLOps platforms or critical ML services, including CI/CD, model serving, monitoring, and incident management. Proven ability to design, implement, and operate technical frameworks for evaluating the commercial impact of machine learning systems in production. Effective collaboration with Data Scientists across the end to end ML lifecycle. Experience working in Agile, cross functional squads. Insurance or financial services experience is a plus but not essential. Technical Skills Strong Python in a machine learning engineering context, with solid software engineering fundamentals (OOP, testing, design patterns). Production ML systems: Experience deploying, monitoring, and maintaining ML models in live environments. Cloud & infrastructure: Hands on experience with a major cloud platform (GCP, AWS, or Azure), including containerised deployments. MLOps & CI/CD: Experience with CI/CD pipelines, Git based workflows, and Infrastructure as Code (e.g. Terraform). Operational excellence: Understanding of API operations, monitoring, logging, and reliability considerations for ML services. Data & integration: Working knowledge of SQL and integrating ML services into wider data and application ecosystems. Why Join Us? This is an opportunity to shape the future of machine learning engineering at Hiscox, build a high performing sub chapter, and influence strategic decisions, while staying close to the craft you love. You'll have the autonomy to set standards, mentor talent, and explore emerging technologies, all within a collaborative and forward thinking environment.
27/06/2026
Full time
Role Purpose As a Lead Machine Learning Engineer (MLE) at Hiscox, you will shape and scale our Machine Learning Engineering capability and ensure the successful deployment and operation of ML in production. You will lead the MLE sub chapter, line manage Machine Learning Engineers, and partner closely with the Head of Data Science, the Data Science sub chapters and Platform/Group teams to enable scalable, reusable, and well governed ML solutions. You will be accountable for the MLOps platform, ensuring it is reliable, secure, and continuously evolved and for ensuring our business unit ships ML to production in a scalable way that is reusable across value streams, enabling efficient model maintenance, monitoring, and lifecycle management. Combining deep technical expertise with leadership, you will set standards, uplift capability, and enable squads to deliver robust, production grade ML systems. Responsibilities People Leadership: Manage and grow talent; set objectives, conduct performance reviews, and guide career progression for the MLE sub chapter. Foster a strong engineering culture: Promote collaboration, psychological safety, and high standards of quality and reliability. Provide coaching and mentorship: Support technical and professional development of Machine Learning Engineers. Strategic Capability Development: Define and evolve chapter strategy; align sub chapter goals with chapter and organisational objectives. Shape technical direction: Establish standards for ML engineering, deployment patterns, and MLOps. Drive upskilling and cross skilling: Build capability in production ML, platform usage, and software engineering best practices. Technical Enablement & Platform Ownership: Own and evolve the MLOps platform; ensure it is reliable, secure, and scalable. Enable scalable and reusable ML delivery: Ensure ML solutions for the business unit are deployable across value streams and efficient to operate. Lead technical spikes and proof of concepts: De risk architectural decisions and explore new tools and approaches. Governance & Standards: Ensure compliance, security, architecture, and operational standards. Define guardrails for production ML systems covering deployment, monitoring, retraining, and decommissioning in collaboration with Data Science. Collaboration & Influence: Partner closely with the Data Science sub chapters and delivery team to ensure effective handover from experimentation to production. Represent Machine Learning Engineering in strategic forums and advocate for platforms, tooling, and scalable ML practices. Qualifications Bachelor's or Master's in Computer Science, Engineering, or a related quantitative field (or equivalent experience). Experience as a Senior/Lead Machine Learning Engineer delivering production ML systems at scale. Solid understanding of core data science concepts, including supervised and unsupervised learning, feature engineering, and model evaluation. Working knowledge of statistical concepts and model evaluation techniques sufficient to review, validate, and productionise data science work. Proven line management and/or technical mentorship of engineers; building capability and setting standards. Demonstrated ownership of MLOps platforms or critical ML services, including CI/CD, model serving, monitoring, and incident management. Proven ability to design, implement, and operate technical frameworks for evaluating the commercial impact of machine learning systems in production. Effective collaboration with Data Scientists across the end to end ML lifecycle. Experience working in Agile, cross functional squads. Insurance or financial services experience is a plus but not essential. Technical Skills Strong Python in a machine learning engineering context, with solid software engineering fundamentals (OOP, testing, design patterns). Production ML systems: Experience deploying, monitoring, and maintaining ML models in live environments. Cloud & infrastructure: Hands on experience with a major cloud platform (GCP, AWS, or Azure), including containerised deployments. MLOps & CI/CD: Experience with CI/CD pipelines, Git based workflows, and Infrastructure as Code (e.g. Terraform). Operational excellence: Understanding of API operations, monitoring, logging, and reliability considerations for ML services. Data & integration: Working knowledge of SQL and integrating ML services into wider data and application ecosystems. Why Join Us? This is an opportunity to shape the future of machine learning engineering at Hiscox, build a high performing sub chapter, and influence strategic decisions, while staying close to the craft you love. You'll have the autonomy to set standards, mentor talent, and explore emerging technologies, all within a collaborative and forward thinking environment.
Client Server Ltd. is seeking a Lead Software Engineer / Developer / Consultant in London to architect AI solutions and drive impactful outcomes. The role involves leading client projects, deploying multi-modal LLMs, and collaborating within a diverse team with a hybrid work policy. The ideal candidate will have a 2.1 degree in a relevant field and substantial experience with AI technologies, particularly in deploying scalable MLOps and advanced engineering practices. Competitive salary up to £125k is offered.
27/06/2026
Full time
Client Server Ltd. is seeking a Lead Software Engineer / Developer / Consultant in London to architect AI solutions and drive impactful outcomes. The role involves leading client projects, deploying multi-modal LLMs, and collaborating within a diverse team with a hybrid work policy. The ideal candidate will have a 2.1 degree in a relevant field and substantial experience with AI technologies, particularly in deploying scalable MLOps and advanced engineering practices. Competitive salary up to £125k is offered.
London, Greater London £100k - £125k per year Lead Software Engineer / Developer / Consultant (Python AI LLM) London / WFH to £125k Are you an experienced Software Engineer with a strong knowledge of AI, LLMs and agentic coding? You could be progressing your career at a global finance technology consultancy, working with clients including global Investment Banks and financial services organisations. What's in it for you: Salary to £125k Pension, Life Assurance, Income Protection Private medical care for you and your family, including mental health Travel Insurance Charitable giving Gym membership for you and your family Your role: As a Lead Software Engineer you will architect AI solutions, embed them within enterprise environments and drive impactful outcomes through advanced engineering, scalable pipelines and deep cross-functional collaboration. This is a highly technical role where you'll be leading client projects, productionising systems and running multi-modal LLMs, using your expertise to build and deploy cutting-edge generative AI and agentic systems across the financial services sector. Location / WFH: There's a hybrid work from home policy with three days a week in the London, City office (or at client sites), you'll join a friendly, diverse, upbeat team. About you: You have achieved a 2.1 or above bachelor's degree in Computer Science, AI or related STEM disciplines You have hands on experience deploying LLMs and multi modal models at scale in production You have a strong understanding of scalable MLOps, observability and cloud native AI deployment You have strong Python coding skills and API development skills You're collaborative and pragmatic with advanced stakeholder communication, problem solving and project management skills in Agile environments Experience with any of the following is advantageous: agentic frameworks (e.g., LangChain, LlamaIndex), deep learning frameworks, Langfuse, Langsmith, MCP (Model Context Protocol), bias mitigation techniques Apply now to find out more about this Lead Software Engineer / Developer / Consultant (Python AI LLM) opportunity.
27/06/2026
Full time
London, Greater London £100k - £125k per year Lead Software Engineer / Developer / Consultant (Python AI LLM) London / WFH to £125k Are you an experienced Software Engineer with a strong knowledge of AI, LLMs and agentic coding? You could be progressing your career at a global finance technology consultancy, working with clients including global Investment Banks and financial services organisations. What's in it for you: Salary to £125k Pension, Life Assurance, Income Protection Private medical care for you and your family, including mental health Travel Insurance Charitable giving Gym membership for you and your family Your role: As a Lead Software Engineer you will architect AI solutions, embed them within enterprise environments and drive impactful outcomes through advanced engineering, scalable pipelines and deep cross-functional collaboration. This is a highly technical role where you'll be leading client projects, productionising systems and running multi-modal LLMs, using your expertise to build and deploy cutting-edge generative AI and agentic systems across the financial services sector. Location / WFH: There's a hybrid work from home policy with three days a week in the London, City office (or at client sites), you'll join a friendly, diverse, upbeat team. About you: You have achieved a 2.1 or above bachelor's degree in Computer Science, AI or related STEM disciplines You have hands on experience deploying LLMs and multi modal models at scale in production You have a strong understanding of scalable MLOps, observability and cloud native AI deployment You have strong Python coding skills and API development skills You're collaborative and pragmatic with advanced stakeholder communication, problem solving and project management skills in Agile environments Experience with any of the following is advantageous: agentic frameworks (e.g., LangChain, LlamaIndex), deep learning frameworks, Langfuse, Langsmith, MCP (Model Context Protocol), bias mitigation techniques Apply now to find out more about this Lead Software Engineer / Developer / Consultant (Python AI LLM) opportunity.
Who We Are Boston Consulting Group partners with leaders in business and society to tackle their most important challenges and capture their greatest opportunities. BCG was the pioneer in business strategy when it was founded in 1963. Today, we help clients with total transformation-inspiring complex change, enabling organizations to grow, building competitive advantage, and driving bottom line impact. To succeed, organizations must blend digital and human capabilities. Our diverse, global teams bring deep industry and functional expertise and a range of perspectives to spark change. BCG delivers solutions through leading edge management consulting along with technology and design, corporate and digital ventures-and business purpose. We work in a uniquely collaborative model across the firm and throughout all levels of the client organization, generating results that allow our clients to thrive. What You'll Do BCG is building the next generation of AI native platforms, enabling advanced reasoning systems, autonomous agents, and enterprise scale GenAI capabilities. As a Platform Team Lead (PTL) Gen AI Platforms and Agent Development Kit, you will play a defining role in shaping the core intelligence layer that powers BCG AI solutions globally. This is a rare opportunity to lead at the forefront of AI platform engineering - architecting the systems, tools, and frameworks that hundreds of teams will rely on to innovate, scale, and deliver impact. You will set the strategy, lead high performing engineering and platform squads, and bring to life a world class AI platform that champions safety, performance, scale and responsible innovation/ RAI. As a PTL, you will drive innovation, collaborate across global teams, and shape the roadmaps that keep BCG at the absolute forefront of AI platforms, capabilities and best practices of building AI/ Agentic solutions at scale. If you are energised by complex technical challenges, enterprise scale transformation, and building platforms that change how organisations operate, this role offers unmatched scope and influence. Among your responsibilities, you will: Lead the Strategy and Execution for the BCG's Core AI/ Intelligence Layer Own and evolve the Gen (AI) platform vision and agentic systems, including LLM orchestration, contextual memory, and semantic knowledge layers. Shape the roadmap for the Platform AI/ Agent Development Kit (ADK) - the core toolset powering developer and team adoption across BCG. Lead Gen (AI) platform engineering teams and operating model. Scale GenAI capabilities firm wide, across Core IT and business use cases. Architecting Scalable, AI Native Systems Design scalable, secure, AI first, cloud native platform components that support advanced reasoning, long term memory, and multimodal insights. Doing so by leveraging BCG's cloud/ hyper saler & vendor partnerships (AWS, GCP and Azure) Define AI solution archetypes for use cases teams to effectively use the platform capabilities with well defined, reusable accelerators, SDK and tool kits. Govern platform wide design decisions to ensure safety, scalability, interoperability and implementation of responsible AI standards. Own cross functional alignment with Data, Security, Capabilities Build, Infrastructure, and business stakeholders Build and Lead High Performing Teams Lead engineering, architecture, and platform teams with a culture of excellence, innovation, and accountability. Coach and mentor senior talent; champion strong engineering practices and high quality delivery. Delivery & Operational Excellence Own end to end delivery of capabilities & components and services owned by the platform teams. Establish and run enterprise grade AI observability frameworks to monitor performance, safety, and interpretability. Continuously enhance LLM Ops, Evaluation and Quality pipelines. Ensure robust AIOps/DevSecOps, CI/CD, Infrastructure as Code, and automated delivery pipelines. What You'll Bring Leadership & Delivery Over 15 years of experience in engineering leadership, platform or product ownership, or technical programme delivery in large enterprise. At least 5 years in AI and Gen AI related experience. 3+ years as Senior Director or Equivalent in software/AI engineering or equivalent. Demonstrated success leading multi disciplinary teams (engineering, product, architecture, data). Evidence of innovation in building/operationalising AI / GenAI or emerging technology platforms. Technical Expertise Masters or Bachelor's in AI/ Computer Science & Engineering or equivalent work experience. Proven success in architecting enterprise scale AI platforms using modern AI native/ cloud native stacks. Deep experience architecting, applying and deploying LLM-based systems, generative models, agent frameworks, and scalable AI/ML platforms. Mastery of enterprise cloud stacks (AWS/GCP/Azure), vector DBs, Knowledge Graphs, contextual memory, distributed systems, MLOps/ LLMOps, and infrastructure automation. Additional info YOUR TRAVEL Mostly from the BCG office, occasionally work at other BCG offices. Boston Consulting Group is an Equal Opportunity Employer. All qualified applicants will receive consideration for employment without regard to race, color, age, religion, sex, sexual orientation, gender identity / expression, national origin, disability, protected veteran status, or any other characteristic protected under national, provincial, or local law, where applicable, and those with criminal histories will be considered in a manner consistent with applicable state and local laws. BCG is an E - Verify Employer. Click here for more information on E-Verify.
27/06/2026
Full time
Who We Are Boston Consulting Group partners with leaders in business and society to tackle their most important challenges and capture their greatest opportunities. BCG was the pioneer in business strategy when it was founded in 1963. Today, we help clients with total transformation-inspiring complex change, enabling organizations to grow, building competitive advantage, and driving bottom line impact. To succeed, organizations must blend digital and human capabilities. Our diverse, global teams bring deep industry and functional expertise and a range of perspectives to spark change. BCG delivers solutions through leading edge management consulting along with technology and design, corporate and digital ventures-and business purpose. We work in a uniquely collaborative model across the firm and throughout all levels of the client organization, generating results that allow our clients to thrive. What You'll Do BCG is building the next generation of AI native platforms, enabling advanced reasoning systems, autonomous agents, and enterprise scale GenAI capabilities. As a Platform Team Lead (PTL) Gen AI Platforms and Agent Development Kit, you will play a defining role in shaping the core intelligence layer that powers BCG AI solutions globally. This is a rare opportunity to lead at the forefront of AI platform engineering - architecting the systems, tools, and frameworks that hundreds of teams will rely on to innovate, scale, and deliver impact. You will set the strategy, lead high performing engineering and platform squads, and bring to life a world class AI platform that champions safety, performance, scale and responsible innovation/ RAI. As a PTL, you will drive innovation, collaborate across global teams, and shape the roadmaps that keep BCG at the absolute forefront of AI platforms, capabilities and best practices of building AI/ Agentic solutions at scale. If you are energised by complex technical challenges, enterprise scale transformation, and building platforms that change how organisations operate, this role offers unmatched scope and influence. Among your responsibilities, you will: Lead the Strategy and Execution for the BCG's Core AI/ Intelligence Layer Own and evolve the Gen (AI) platform vision and agentic systems, including LLM orchestration, contextual memory, and semantic knowledge layers. Shape the roadmap for the Platform AI/ Agent Development Kit (ADK) - the core toolset powering developer and team adoption across BCG. Lead Gen (AI) platform engineering teams and operating model. Scale GenAI capabilities firm wide, across Core IT and business use cases. Architecting Scalable, AI Native Systems Design scalable, secure, AI first, cloud native platform components that support advanced reasoning, long term memory, and multimodal insights. Doing so by leveraging BCG's cloud/ hyper saler & vendor partnerships (AWS, GCP and Azure) Define AI solution archetypes for use cases teams to effectively use the platform capabilities with well defined, reusable accelerators, SDK and tool kits. Govern platform wide design decisions to ensure safety, scalability, interoperability and implementation of responsible AI standards. Own cross functional alignment with Data, Security, Capabilities Build, Infrastructure, and business stakeholders Build and Lead High Performing Teams Lead engineering, architecture, and platform teams with a culture of excellence, innovation, and accountability. Coach and mentor senior talent; champion strong engineering practices and high quality delivery. Delivery & Operational Excellence Own end to end delivery of capabilities & components and services owned by the platform teams. Establish and run enterprise grade AI observability frameworks to monitor performance, safety, and interpretability. Continuously enhance LLM Ops, Evaluation and Quality pipelines. Ensure robust AIOps/DevSecOps, CI/CD, Infrastructure as Code, and automated delivery pipelines. What You'll Bring Leadership & Delivery Over 15 years of experience in engineering leadership, platform or product ownership, or technical programme delivery in large enterprise. At least 5 years in AI and Gen AI related experience. 3+ years as Senior Director or Equivalent in software/AI engineering or equivalent. Demonstrated success leading multi disciplinary teams (engineering, product, architecture, data). Evidence of innovation in building/operationalising AI / GenAI or emerging technology platforms. Technical Expertise Masters or Bachelor's in AI/ Computer Science & Engineering or equivalent work experience. Proven success in architecting enterprise scale AI platforms using modern AI native/ cloud native stacks. Deep experience architecting, applying and deploying LLM-based systems, generative models, agent frameworks, and scalable AI/ML platforms. Mastery of enterprise cloud stacks (AWS/GCP/Azure), vector DBs, Knowledge Graphs, contextual memory, distributed systems, MLOps/ LLMOps, and infrastructure automation. Additional info YOUR TRAVEL Mostly from the BCG office, occasionally work at other BCG offices. Boston Consulting Group is an Equal Opportunity Employer. All qualified applicants will receive consideration for employment without regard to race, color, age, religion, sex, sexual orientation, gender identity / expression, national origin, disability, protected veteran status, or any other characteristic protected under national, provincial, or local law, where applicable, and those with criminal histories will be considered in a manner consistent with applicable state and local laws. BCG is an E - Verify Employer. Click here for more information on E-Verify.
Summary The AI Innovation and Solutions (AIS) team operates with the speed and spirit of a startup, focused on rapidly prototyping and building production grade, cloud native AI applications that integrate cutting edge AI capabilities to directly address the critical needs of our businesses. Our primary goal is to demonstrate the transformative potential of AI within the firm through accelerated application delivery, rapidly deploying impactful solutions, and then seamlessly transferring the application code, cloud integration patterns, robust data models, and operational knowledge to respective business and engineering teams. This hands on engineering role is pivotal in shaping the future of AI adoption at Goldman Sachs by building reliable, highly scalable, cloud optimized AI powered products and fostering a culture of innovation and rapid, continuous delivery. As an AI Application Engineer, you will be instrumental in designing, building, and deploying end to end, cloud native AI applications that leverage advanced AI/Machine Learning solutions to drive tangible business value. You will thrive in a fast paced environment, leveraging your expertise to translate complex business challenges and customer needs into actionable cloud based application architectures, optimized data models, and technical specifications that incorporate AI capabilities, and then implement and deliver these systems with a focus on speed, reliability, and operational excellence. Key Responsibilities Rapid Prototyping & Application Development: Lead the end to end development of applications that integrate and leverage AI/ML models, from architectural design, data schema design, data pipeline construction, and rapid prototyping to initial deployment and operationalization, utilizing cloud native services (e.g., serverless, containerization, managed AI/ML platforms) and CI/CD pipelines for accelerated delivery. Implement robust MLOps practices to streamline model deployment, monitoring, and lifecycle management in cloud environments, including data versioning, feature store integration, and data pipeline management. Business Partnership & Solution Architecture: Collaborate closely with business and engineering teams to deeply understand their challenges and customer needs, identify high impact opportunities to integrate AI capabilities into applications, and translate business requirements into robust cloud optimized application architectures, scalable data models, and technical specifications for AI powered solutions, considering scalability, cost efficiency, security, and data governance principles. Solution Implementation & Delivery: Architect, implement, and deliver scalable, robust, and maintainable cloud native AI applications that consume and operationalize AI solutions based on defined technical specifications and architectures, ensuring seamless integration with existing systems and workflows within the Goldman Sachs ecosystem. Apply strong software engineering principles, data modeling best practices (e.g., relational, NoSQL, graph), DevOps/MLOps best practices, and cloud security standards. Drive automation of deployment, testing, and monitoring processes to ensure rapid and reliable delivery of AI applications. Knowledge Transfer & Enablement: Facilitate effective knowledge transfer through comprehensive documentation, training sessions, mentorship, and pair programming, empowering receiving teams to take ownership and continue the development and maintenance of AI powered applications. Technology & Innovation Leadership: Stay abreast of the latest advancements in application development, system integration, AI/ML technologies, data management platforms, and operational best practices, continuously evaluating and recommending new tools, techniques, and architectural patterns to drive innovation in AI application delivery. Qualifications Bachelor's or Master's degree in Computer Science, Software Engineering, or a related quantitative field. 9+ years of hands on software engineering experience, with a proven track record of building and deploying robust applications, and significant experience integrating AI/ML models. Demonstrated experience building and deploying end to end applications that leverage LLMs and related frameworks. This includes experience with prompt engineering, API integration, and working with agentic frameworks. Strong proficiency in programming languages such as Python, Java, or Go, along with experience integrating with relevant AI/ML frameworks (e.g., TensorFlow, PyTorch). Proven ability to translate complex business requirements into well defined, cloud optimized application architectures, scalable data models (e.g., relational, NoSQL, graph), and technical specifications for AI powered systems, and to subsequently implement and accelerate delivery of robust, production ready systems based on these designs. Extensive experience with major cloud platforms (e.g., AWS, Azure, GCP), including cloud native services (serverless, containerization, managed AI/ML platforms), and a strong command of DevOps/MLOps best practices for automated deployment, monitoring, lifecycle management, data pipeline orchestration, and cloud security standards. Excellent communication capabilities, with the ability to articulate complex technical concepts to both technical and non technical stakeholders across all levels of the organization. Strong collaboration and interpersonal skills, with a passion for mentoring and enabling others. Proven ability to lead or significantly contribute to cross functional projects. Productionize LLMs: Build evaluation framework for open source and foundational LLMs; implement retrieval pipelines, prompt synthesis, response validation, and self correction loops tailored to production operations. Integrate with runtime ecosystems: Connect agents to observability, incident management, and deployment systems to enable automated diagnostics, runbook execution, remediation, and post incident summarization with full traceability. Collaborate directly with users: Partner with production engineers, and application teams to translate production pain points into agentic AI roadmaps; define objective functions linked to reliability, risk reduction, and cost; and deliver auditable, business aligned outcomes. Scale and performance: Optimize cost and latency via prompt engineering, context management, caching, model routing, and distillation; leverage batching, streaming, and parallel tool calls to meet stringent SLOs under real world load. Build agentic AI systems: Design and implement tool calling agents that combine retrieval, structured reasoning, and secure action execution (function calling, change orchestration, policy enforcement) following MCP protocol. Integrate with runtime ecosystems: Connect agents to observability, incident management, and deployment systems to enable automated diagnostics, runbook execution, remediation, and post incident summarization with full traceability. ABOUT GOLDMAN SACHS At Goldman Sachs, we commit our people, capital and ideas to help our clients, shareholders and the communities we serve to grow. Founded in 1869, we are a leading global investment banking, securities and investment management firm. Headquartered in New York, we maintain offices around the world. We believe who you are makes you better at what you do. We're committed to fostering and advancing diversity and inclusion in our own workplace and beyond by ensuring every individual within our firm has a number of opportunities to grow professionally and personally, from our training and development opportunities and firm wide networks to benefits, wellness and personal finance offerings and mindfulness programs. Learn more about our culture, benefits, and people at The Goldman Sachs Group, Inc., 2023. All rights reserved. Goldman Sachs is an equal opportunity employer and does not discriminate on the basis of race, color, religion, sex, national origin, age, veterans status, disability, or any other characteristic protected by applicable law.
27/06/2026
Full time
Summary The AI Innovation and Solutions (AIS) team operates with the speed and spirit of a startup, focused on rapidly prototyping and building production grade, cloud native AI applications that integrate cutting edge AI capabilities to directly address the critical needs of our businesses. Our primary goal is to demonstrate the transformative potential of AI within the firm through accelerated application delivery, rapidly deploying impactful solutions, and then seamlessly transferring the application code, cloud integration patterns, robust data models, and operational knowledge to respective business and engineering teams. This hands on engineering role is pivotal in shaping the future of AI adoption at Goldman Sachs by building reliable, highly scalable, cloud optimized AI powered products and fostering a culture of innovation and rapid, continuous delivery. As an AI Application Engineer, you will be instrumental in designing, building, and deploying end to end, cloud native AI applications that leverage advanced AI/Machine Learning solutions to drive tangible business value. You will thrive in a fast paced environment, leveraging your expertise to translate complex business challenges and customer needs into actionable cloud based application architectures, optimized data models, and technical specifications that incorporate AI capabilities, and then implement and deliver these systems with a focus on speed, reliability, and operational excellence. Key Responsibilities Rapid Prototyping & Application Development: Lead the end to end development of applications that integrate and leverage AI/ML models, from architectural design, data schema design, data pipeline construction, and rapid prototyping to initial deployment and operationalization, utilizing cloud native services (e.g., serverless, containerization, managed AI/ML platforms) and CI/CD pipelines for accelerated delivery. Implement robust MLOps practices to streamline model deployment, monitoring, and lifecycle management in cloud environments, including data versioning, feature store integration, and data pipeline management. Business Partnership & Solution Architecture: Collaborate closely with business and engineering teams to deeply understand their challenges and customer needs, identify high impact opportunities to integrate AI capabilities into applications, and translate business requirements into robust cloud optimized application architectures, scalable data models, and technical specifications for AI powered solutions, considering scalability, cost efficiency, security, and data governance principles. Solution Implementation & Delivery: Architect, implement, and deliver scalable, robust, and maintainable cloud native AI applications that consume and operationalize AI solutions based on defined technical specifications and architectures, ensuring seamless integration with existing systems and workflows within the Goldman Sachs ecosystem. Apply strong software engineering principles, data modeling best practices (e.g., relational, NoSQL, graph), DevOps/MLOps best practices, and cloud security standards. Drive automation of deployment, testing, and monitoring processes to ensure rapid and reliable delivery of AI applications. Knowledge Transfer & Enablement: Facilitate effective knowledge transfer through comprehensive documentation, training sessions, mentorship, and pair programming, empowering receiving teams to take ownership and continue the development and maintenance of AI powered applications. Technology & Innovation Leadership: Stay abreast of the latest advancements in application development, system integration, AI/ML technologies, data management platforms, and operational best practices, continuously evaluating and recommending new tools, techniques, and architectural patterns to drive innovation in AI application delivery. Qualifications Bachelor's or Master's degree in Computer Science, Software Engineering, or a related quantitative field. 9+ years of hands on software engineering experience, with a proven track record of building and deploying robust applications, and significant experience integrating AI/ML models. Demonstrated experience building and deploying end to end applications that leverage LLMs and related frameworks. This includes experience with prompt engineering, API integration, and working with agentic frameworks. Strong proficiency in programming languages such as Python, Java, or Go, along with experience integrating with relevant AI/ML frameworks (e.g., TensorFlow, PyTorch). Proven ability to translate complex business requirements into well defined, cloud optimized application architectures, scalable data models (e.g., relational, NoSQL, graph), and technical specifications for AI powered systems, and to subsequently implement and accelerate delivery of robust, production ready systems based on these designs. Extensive experience with major cloud platforms (e.g., AWS, Azure, GCP), including cloud native services (serverless, containerization, managed AI/ML platforms), and a strong command of DevOps/MLOps best practices for automated deployment, monitoring, lifecycle management, data pipeline orchestration, and cloud security standards. Excellent communication capabilities, with the ability to articulate complex technical concepts to both technical and non technical stakeholders across all levels of the organization. Strong collaboration and interpersonal skills, with a passion for mentoring and enabling others. Proven ability to lead or significantly contribute to cross functional projects. Productionize LLMs: Build evaluation framework for open source and foundational LLMs; implement retrieval pipelines, prompt synthesis, response validation, and self correction loops tailored to production operations. Integrate with runtime ecosystems: Connect agents to observability, incident management, and deployment systems to enable automated diagnostics, runbook execution, remediation, and post incident summarization with full traceability. Collaborate directly with users: Partner with production engineers, and application teams to translate production pain points into agentic AI roadmaps; define objective functions linked to reliability, risk reduction, and cost; and deliver auditable, business aligned outcomes. Scale and performance: Optimize cost and latency via prompt engineering, context management, caching, model routing, and distillation; leverage batching, streaming, and parallel tool calls to meet stringent SLOs under real world load. Build agentic AI systems: Design and implement tool calling agents that combine retrieval, structured reasoning, and secure action execution (function calling, change orchestration, policy enforcement) following MCP protocol. Integrate with runtime ecosystems: Connect agents to observability, incident management, and deployment systems to enable automated diagnostics, runbook execution, remediation, and post incident summarization with full traceability. ABOUT GOLDMAN SACHS At Goldman Sachs, we commit our people, capital and ideas to help our clients, shareholders and the communities we serve to grow. Founded in 1869, we are a leading global investment banking, securities and investment management firm. Headquartered in New York, we maintain offices around the world. We believe who you are makes you better at what you do. We're committed to fostering and advancing diversity and inclusion in our own workplace and beyond by ensuring every individual within our firm has a number of opportunities to grow professionally and personally, from our training and development opportunities and firm wide networks to benefits, wellness and personal finance offerings and mindfulness programs. Learn more about our culture, benefits, and people at The Goldman Sachs Group, Inc., 2023. All rights reserved. Goldman Sachs is an equal opportunity employer and does not discriminate on the basis of race, color, religion, sex, national origin, age, veterans status, disability, or any other characteristic protected by applicable law.
Founding Systems Engineer (Infrastructure) London • 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 Systems Engineer, you will lead our ML Infrastructure team, driving DevOps, MLOps, and Agent Ops across both R&D and production environments. You will own the automation of release and evaluation processes and collaborate closely with cross-functional teams to support their projects. This is a critical role for a builder who thrives at the intersection of ML research infrastructure and production systems, and wants to define the engineering culture of a fast-paced AI company from the ground up. What You'll Build ML Infrastructure Leadership: Lead the ML Infrastructure team working on DevOps, MLOps, and Agent Ops for both R&D and production environments. Release & Evaluation Automation: Automate the release and evaluation processes for research and production, ensuring reliable and efficient delivery of ML systems. Cross-Functional Collaboration: Collaborate with cross-functional teams and support their projects, acting as a key enabler across the organisation. What We Are Looking For MLOps & DevOps Tooling: Proven track record of working with systems such as ArgoCD, Kargo, Jenkins, Vertex AI, SageMaker, and similar platforms. ML Infrastructure Experience: Proven track record of working on ML research and production infrastructure. Infrastructure as Code: Knowledge of IaC tools such as Terraform and Helm. Cloud Expertise: Excellent familiarity with at least one of the hyperscaler clouds (GCP, AWS, Azure), and familiarity with the others. Engineering Excellence: Excellent software engineering and problem-solving skills. Communication: Excellent interpersonal and communication skills. Why Join Us Founding Equity: Significant ownership in a company tackling the next layer of the AI stack. Technical Challenge: Solve novel infrastructure problems related to secure agentic execution and "orgs in a box." 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. Apply for this role.
27/06/2026
Full time
Founding Systems Engineer (Infrastructure) London • 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 Systems Engineer, you will lead our ML Infrastructure team, driving DevOps, MLOps, and Agent Ops across both R&D and production environments. You will own the automation of release and evaluation processes and collaborate closely with cross-functional teams to support their projects. This is a critical role for a builder who thrives at the intersection of ML research infrastructure and production systems, and wants to define the engineering culture of a fast-paced AI company from the ground up. What You'll Build ML Infrastructure Leadership: Lead the ML Infrastructure team working on DevOps, MLOps, and Agent Ops for both R&D and production environments. Release & Evaluation Automation: Automate the release and evaluation processes for research and production, ensuring reliable and efficient delivery of ML systems. Cross-Functional Collaboration: Collaborate with cross-functional teams and support their projects, acting as a key enabler across the organisation. What We Are Looking For MLOps & DevOps Tooling: Proven track record of working with systems such as ArgoCD, Kargo, Jenkins, Vertex AI, SageMaker, and similar platforms. ML Infrastructure Experience: Proven track record of working on ML research and production infrastructure. Infrastructure as Code: Knowledge of IaC tools such as Terraform and Helm. Cloud Expertise: Excellent familiarity with at least one of the hyperscaler clouds (GCP, AWS, Azure), and familiarity with the others. Engineering Excellence: Excellent software engineering and problem-solving skills. Communication: Excellent interpersonal and communication skills. Why Join Us Founding Equity: Significant ownership in a company tackling the next layer of the AI stack. Technical Challenge: Solve novel infrastructure problems related to secure agentic execution and "orgs in a box." 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. Apply for this role.
DV Cleared Senior AI Engineer Location: London (Hybrid) Contract Type: Contract Day rate: 700 Outside Clearance Required: Active UK DV Clearance (Mandatory) The Opportunity We are partnering with a premier UK deep-tech venture that sits at the cutting edge of AI, robotics, and national security. They build advanced software frameworks that fuse complex, multi-modal data streams (sensor feeds, telemetry, imagery, and text) to enable real-time decision-making in high-stakes, mission-critical environments. With multiple positions open due to rapid growth, they are looking for production-focused AI Engineers who want high ownership, fast-paced delivery, and the chance to deploy agentic systems that protect critical national infrastructure and save lives. Key Responsibilities Architect & Build: Design, optimize, and scale robust multi-agent AI pipelines and orchestration frameworks. Model Integration: Integrate LLMs and vision-language models (VLMs) into workflows optimized for reasoning, search, and autonomous task execution. Secure Deployment: Package and deploy AI systems into highly secure, cloud, on-premises, and air-gapped environments. Production MLOps: Build end-to-end data ingestion and inference pipelines with a heavy focus on system reliability over raw speed to market. Observability & Evaluation: Implement monitoring tooling to track agent behavior, model performance, drift, and unexpected failure modes. Technical Leadership: Serve as a subject matter expert for agentic AI, helping establish engineering patterns and mentoring junior developers. Technical Requirements Must-Have: Active UK DV Clearance. (Applications without this cannot be considered). Commercial AI Delivery: A proven track record of shipping multi-agent or agentic AI frameworks into live production environments. Core Software Engineering: Exceptional Python skills alongside hands-on experience with LLM orchestration tools (e.g., LangGraph, LangChain, Haystack, or similar). Modern DevOps: Strong experience with Docker, Git, and cloud infrastructure. Secure Architecture: Solid comprehension of secure-by-design principles and deployment patterns for sovereign clouds or disconnected networks. Great-to-Have: Experience with edge computing, offline AI deployments, or local model execution. Familiarity with Kubernetes (EKS/OpenShift) for container management and application monitoring. Knowledge of advanced agent orchestration protocols (e.g., A2A communication) and Model Context Protocols (MCPs). Familiarity with secure development frameworks (OWASP, NIST, ISO 27001). Background working in Defence, GovTech, aerospace, or similarly regulated sectors. JBRP1_UKTJ
27/06/2026
Full time
DV Cleared Senior AI Engineer Location: London (Hybrid) Contract Type: Contract Day rate: 700 Outside Clearance Required: Active UK DV Clearance (Mandatory) The Opportunity We are partnering with a premier UK deep-tech venture that sits at the cutting edge of AI, robotics, and national security. They build advanced software frameworks that fuse complex, multi-modal data streams (sensor feeds, telemetry, imagery, and text) to enable real-time decision-making in high-stakes, mission-critical environments. With multiple positions open due to rapid growth, they are looking for production-focused AI Engineers who want high ownership, fast-paced delivery, and the chance to deploy agentic systems that protect critical national infrastructure and save lives. Key Responsibilities Architect & Build: Design, optimize, and scale robust multi-agent AI pipelines and orchestration frameworks. Model Integration: Integrate LLMs and vision-language models (VLMs) into workflows optimized for reasoning, search, and autonomous task execution. Secure Deployment: Package and deploy AI systems into highly secure, cloud, on-premises, and air-gapped environments. Production MLOps: Build end-to-end data ingestion and inference pipelines with a heavy focus on system reliability over raw speed to market. Observability & Evaluation: Implement monitoring tooling to track agent behavior, model performance, drift, and unexpected failure modes. Technical Leadership: Serve as a subject matter expert for agentic AI, helping establish engineering patterns and mentoring junior developers. Technical Requirements Must-Have: Active UK DV Clearance. (Applications without this cannot be considered). Commercial AI Delivery: A proven track record of shipping multi-agent or agentic AI frameworks into live production environments. Core Software Engineering: Exceptional Python skills alongside hands-on experience with LLM orchestration tools (e.g., LangGraph, LangChain, Haystack, or similar). Modern DevOps: Strong experience with Docker, Git, and cloud infrastructure. Secure Architecture: Solid comprehension of secure-by-design principles and deployment patterns for sovereign clouds or disconnected networks. Great-to-Have: Experience with edge computing, offline AI deployments, or local model execution. Familiarity with Kubernetes (EKS/OpenShift) for container management and application monitoring. Knowledge of advanced agent orchestration protocols (e.g., A2A communication) and Model Context Protocols (MCPs). Familiarity with secure development frameworks (OWASP, NIST, ISO 27001). Background working in Defence, GovTech, aerospace, or similarly regulated sectors. JBRP1_UKTJ
Who We Are Boston Consulting Group partners with leaders in business and society to tackle their most important challenges and capture their greatest opportunities. BCG was the pioneer in business strategy when it was founded in 1963. Today, we help clients with total transformation-inspiring complex change, enabling organizations to grow, building competitive advantage, and driving bottom-line impact. To succeed, organizations must blend digital and human capabilities. Our diverse, global teams bring deep industry and functional expertise and a range of perspectives to spark change. BCG delivers solutions through leading-edge management consulting along with technology and design, corporate and digital ventures-and business purpose. We work in a uniquely collaborative model across the firm and throughout all levels of the client organization, generating results that allow our clients to thrive. What You'll Do Are you passionate about harnessing the power of Generative AI to solve real-world problems? As a world-renowned and leading AI Consulting firm, we are actively seeking hands-on GenAI experts to join our PSG BI&A Team. As a GenAI IT Senior Data Scientist you will work closely with our Partner Services Group to understand their key challenges, define GenAI products, win buy-in for your recommendations and collaborate with other IT teams to transform stakeholder potentials into performance. Finally, as a GenAI IT Senior Data Scientist, you will contribute to PSG BI&A Data Science expertise and will be responsible for overseeing end-to-end Data Science and GenAI solutions, collaborating closely with the BI&A Squad to deliver on stakeholder objectives. What You'll Bring We're looking for exceptional talent with experience in core Data Science and AI to join us. You will typically have: • +4 years experience in IT strategy and consulting, professional software development or Data Science product organisation. • A bachelor's or master's degree in computer science, Engineering, or a related field. Preferably with a focus on artificial intelligence, machine learning, or data science. • Strong Data Science experience with proficiency in Python, Snowflake, DBT and Tableau with experience working in a Data Engineering team and a proven ability to communicate effectively and provide clear, actionable insights to senior stakeholders • Strong technical expertise in Generative AI, Data Science and Machine Learning. • A strategic thinker, entrepreneurial, able to work creatively and analytically in a problem-solving environment • Outstanding analytical and conceptual skills, strong customer focus and mental agility with a results orientation • Sound understanding of GenAI solution constructs e.g., LLMs, RAG, Guardrails, MLOps and multi-modality • Experience managing and executing data science and AI projects, from ideation to deployment, while ensuring alignment with business objectives and delivering impactful outcomes • Understanding of various GenAI platform & middleware and how they fit in GenAI architecture e.g., AWS Bedrock, Google Vertex, Langchain or LlamaIndex • Able to understand & apply advanced prompt engineering methods and related concepts (RAG, context windows, memory) RAG is a must! • Experience in the organisation of workshops at peer level and facilitating meetings • Ability to work autonomously while contributing effectively as part of a team • Strong business acumen; can frame complex problems in appropriate business contexts • Highly professional and rigorous, results-oriented, driven and hard-working • Have excellent verbal and written communication skills in English • Loyal and reliable, possessing the highest ethical standard • Good interpersonal skills but also judgement independency and autonomy • Ability to propose innovative ideas, build empathy within the firm and win the trust of key stakeholders Who You'll Work With You will be part of the PSG BI&A Squad and our IT Functional Technology team, partnering with the AI Center of Excellence (AI CoE), Genie team, Responsible AI, and Security/Architecture teams. Together, you'll deliver scalable, secure, and innovative GenAI solutions that will transform how PSG teams engage with technology. Boston Consulting Group is an Equal Opportunity Employer. All qualified applicants will receive consideration for employment without regard to race, color, age, religion, sex, sexual orientation, gender identity / expression, national origin, disability, protected veteran status, or any other characteristic protected under national, provincial, or local law, where applicable, and those with criminal histories will be considered in a manner consistent with applicable state and local laws. BCG is an E - Verify Employer. Click here for more information on E-Verify.
26/06/2026
Full time
Who We Are Boston Consulting Group partners with leaders in business and society to tackle their most important challenges and capture their greatest opportunities. BCG was the pioneer in business strategy when it was founded in 1963. Today, we help clients with total transformation-inspiring complex change, enabling organizations to grow, building competitive advantage, and driving bottom-line impact. To succeed, organizations must blend digital and human capabilities. Our diverse, global teams bring deep industry and functional expertise and a range of perspectives to spark change. BCG delivers solutions through leading-edge management consulting along with technology and design, corporate and digital ventures-and business purpose. We work in a uniquely collaborative model across the firm and throughout all levels of the client organization, generating results that allow our clients to thrive. What You'll Do Are you passionate about harnessing the power of Generative AI to solve real-world problems? As a world-renowned and leading AI Consulting firm, we are actively seeking hands-on GenAI experts to join our PSG BI&A Team. As a GenAI IT Senior Data Scientist you will work closely with our Partner Services Group to understand their key challenges, define GenAI products, win buy-in for your recommendations and collaborate with other IT teams to transform stakeholder potentials into performance. Finally, as a GenAI IT Senior Data Scientist, you will contribute to PSG BI&A Data Science expertise and will be responsible for overseeing end-to-end Data Science and GenAI solutions, collaborating closely with the BI&A Squad to deliver on stakeholder objectives. What You'll Bring We're looking for exceptional talent with experience in core Data Science and AI to join us. You will typically have: • +4 years experience in IT strategy and consulting, professional software development or Data Science product organisation. • A bachelor's or master's degree in computer science, Engineering, or a related field. Preferably with a focus on artificial intelligence, machine learning, or data science. • Strong Data Science experience with proficiency in Python, Snowflake, DBT and Tableau with experience working in a Data Engineering team and a proven ability to communicate effectively and provide clear, actionable insights to senior stakeholders • Strong technical expertise in Generative AI, Data Science and Machine Learning. • A strategic thinker, entrepreneurial, able to work creatively and analytically in a problem-solving environment • Outstanding analytical and conceptual skills, strong customer focus and mental agility with a results orientation • Sound understanding of GenAI solution constructs e.g., LLMs, RAG, Guardrails, MLOps and multi-modality • Experience managing and executing data science and AI projects, from ideation to deployment, while ensuring alignment with business objectives and delivering impactful outcomes • Understanding of various GenAI platform & middleware and how they fit in GenAI architecture e.g., AWS Bedrock, Google Vertex, Langchain or LlamaIndex • Able to understand & apply advanced prompt engineering methods and related concepts (RAG, context windows, memory) RAG is a must! • Experience in the organisation of workshops at peer level and facilitating meetings • Ability to work autonomously while contributing effectively as part of a team • Strong business acumen; can frame complex problems in appropriate business contexts • Highly professional and rigorous, results-oriented, driven and hard-working • Have excellent verbal and written communication skills in English • Loyal and reliable, possessing the highest ethical standard • Good interpersonal skills but also judgement independency and autonomy • Ability to propose innovative ideas, build empathy within the firm and win the trust of key stakeholders Who You'll Work With You will be part of the PSG BI&A Squad and our IT Functional Technology team, partnering with the AI Center of Excellence (AI CoE), Genie team, Responsible AI, and Security/Architecture teams. Together, you'll deliver scalable, secure, and innovative GenAI solutions that will transform how PSG teams engage with technology. Boston Consulting Group is an Equal Opportunity Employer. All qualified applicants will receive consideration for employment without regard to race, color, age, religion, sex, sexual orientation, gender identity / expression, national origin, disability, protected veteran status, or any other characteristic protected under national, provincial, or local law, where applicable, and those with criminal histories will be considered in a manner consistent with applicable state and local laws. BCG is an E - Verify Employer. Click here for more information on E-Verify.
Who We Are Boston Consulting Group partners with leaders in business and society to tackle their most important challenges and capture their greatest opportunities. BCG was the pioneer in business strategy when it was founded in 1963. Today, we help clients with total transformation-inspiring complex change, enabling organizations to grow, building competitive advantage, and driving bottom-line impact. To succeed, organizations must blend digital and human capabilities. Our diverse, global teams bring deep industry and functional expertise and a range of perspectives to spark change. BCG delivers solutions through leading-edge management consulting along with technology and design, corporate and digital ventures-and business purpose. We work in a uniquely collaborative model across the firm and throughout all levels of the client organization, generating results that allow our clients to thrive. What You'll Do Are you passionate about harnessing the power of Generative AI to solve real-world problems? As a world-renowned and leading AI Consulting firm, we are actively seeking hands-on GenAI experts to join our PSG BI&A Team. As a GenAI IT Senior Data Scientist you will work closely with our Partner Services Group to understand their key challenges, define GenAI products, win buy-in for your recommendations and collaborate with other IT teams to transform stakeholder potentials into performance. Finally, as a GenAI IT Senior Data Scientist, you will contribute to PSG BI&A Data Science expertise and will be responsible for overseeing end-to-end Data Science and GenAI solutions, collaborating closely with the BI&A Squad to deliver on stakeholder objectives. What You'll Bring We're looking for exceptional talent with experience in core Data Science and AI to join us. You will typically have: • +4 years experience in IT strategy and consulting, professional software development or Data Science product organisation. • A bachelor's or master's degree in computer science, Engineering, or a related field. Preferably with a focus on artificial intelligence, machine learning, or data science. • Strong Data Science experience with proficiency in Python, Snowflake, DBT and Tableau with experience working in a Data Engineering team and a proven ability to communicate effectively and provide clear, actionable insights to senior stakeholders • Strong technical expertise in Generative AI, Data Science and Machine Learning. • A strategic thinker, entrepreneurial, able to work creatively and analytically in a problem-solving environment • Outstanding analytical and conceptual skills, strong customer focus and mental agility with a results orientation • Sound understanding of GenAI solution constructs e.g., LLMs, RAG, Guardrails, MLOps and multi-modality • Experience managing and executing data science and AI projects, from ideation to deployment, while ensuring alignment with business objectives and delivering impactful outcomes • Understanding of various GenAI platform & middleware and how they fit in GenAI architecture e.g., AWS Bedrock, Google Vertex, Langchain or LlamaIndex • Able to understand & apply advanced prompt engineering methods and related concepts (RAG, context windows, memory) RAG is a must! • Experience in the organisation of workshops at peer level and facilitating meetings • Ability to work autonomously while contributing effectively as part of a team • Strong business acumen; can frame complex problems in appropriate business contexts • Highly professional and rigorous, results-oriented, driven and hard-working • Have excellent verbal and written communication skills in English • Loyal and reliable, possessing the highest ethical standard • Good interpersonal skills but also judgement independency and autonomy • Ability to propose innovative ideas, build empathy within the firm and win the trust of key stakeholders Who You'll Work With You will be part of the PSG BI&A Squad and our IT Functional Technology team, partnering with the AI Center of Excellence (AI CoE), Genie team, Responsible AI, and Security/Architecture teams. Together, you'll deliver scalable, secure, and innovative GenAI solutions that will transform how PSG teams engage with technology. Boston Consulting Group is an Equal Opportunity Employer. All qualified applicants will receive consideration for employment without regard to race, color, age, religion, sex, sexual orientation, gender identity / expression, national origin, disability, protected veteran status, or any other characteristic protected under national, provincial, or local law, where applicable, and those with criminal histories will be considered in a manner consistent with applicable state and local laws. BCG is an E - Verify Employer. Click here for more information on E-Verify.
26/06/2026
Full time
Who We Are Boston Consulting Group partners with leaders in business and society to tackle their most important challenges and capture their greatest opportunities. BCG was the pioneer in business strategy when it was founded in 1963. Today, we help clients with total transformation-inspiring complex change, enabling organizations to grow, building competitive advantage, and driving bottom-line impact. To succeed, organizations must blend digital and human capabilities. Our diverse, global teams bring deep industry and functional expertise and a range of perspectives to spark change. BCG delivers solutions through leading-edge management consulting along with technology and design, corporate and digital ventures-and business purpose. We work in a uniquely collaborative model across the firm and throughout all levels of the client organization, generating results that allow our clients to thrive. What You'll Do Are you passionate about harnessing the power of Generative AI to solve real-world problems? As a world-renowned and leading AI Consulting firm, we are actively seeking hands-on GenAI experts to join our PSG BI&A Team. As a GenAI IT Senior Data Scientist you will work closely with our Partner Services Group to understand their key challenges, define GenAI products, win buy-in for your recommendations and collaborate with other IT teams to transform stakeholder potentials into performance. Finally, as a GenAI IT Senior Data Scientist, you will contribute to PSG BI&A Data Science expertise and will be responsible for overseeing end-to-end Data Science and GenAI solutions, collaborating closely with the BI&A Squad to deliver on stakeholder objectives. What You'll Bring We're looking for exceptional talent with experience in core Data Science and AI to join us. You will typically have: • +4 years experience in IT strategy and consulting, professional software development or Data Science product organisation. • A bachelor's or master's degree in computer science, Engineering, or a related field. Preferably with a focus on artificial intelligence, machine learning, or data science. • Strong Data Science experience with proficiency in Python, Snowflake, DBT and Tableau with experience working in a Data Engineering team and a proven ability to communicate effectively and provide clear, actionable insights to senior stakeholders • Strong technical expertise in Generative AI, Data Science and Machine Learning. • A strategic thinker, entrepreneurial, able to work creatively and analytically in a problem-solving environment • Outstanding analytical and conceptual skills, strong customer focus and mental agility with a results orientation • Sound understanding of GenAI solution constructs e.g., LLMs, RAG, Guardrails, MLOps and multi-modality • Experience managing and executing data science and AI projects, from ideation to deployment, while ensuring alignment with business objectives and delivering impactful outcomes • Understanding of various GenAI platform & middleware and how they fit in GenAI architecture e.g., AWS Bedrock, Google Vertex, Langchain or LlamaIndex • Able to understand & apply advanced prompt engineering methods and related concepts (RAG, context windows, memory) RAG is a must! • Experience in the organisation of workshops at peer level and facilitating meetings • Ability to work autonomously while contributing effectively as part of a team • Strong business acumen; can frame complex problems in appropriate business contexts • Highly professional and rigorous, results-oriented, driven and hard-working • Have excellent verbal and written communication skills in English • Loyal and reliable, possessing the highest ethical standard • Good interpersonal skills but also judgement independency and autonomy • Ability to propose innovative ideas, build empathy within the firm and win the trust of key stakeholders Who You'll Work With You will be part of the PSG BI&A Squad and our IT Functional Technology team, partnering with the AI Center of Excellence (AI CoE), Genie team, Responsible AI, and Security/Architecture teams. Together, you'll deliver scalable, secure, and innovative GenAI solutions that will transform how PSG teams engage with technology. Boston Consulting Group is an Equal Opportunity Employer. All qualified applicants will receive consideration for employment without regard to race, color, age, religion, sex, sexual orientation, gender identity / expression, national origin, disability, protected veteran status, or any other characteristic protected under national, provincial, or local law, where applicable, and those with criminal histories will be considered in a manner consistent with applicable state and local laws. BCG is an E - Verify Employer. Click here for more information on E-Verify.
Senior AI Engineer - Permanent - London/Hybrid Permanent Hybrid in Central London Competitive Salary Key Responsibilities Technical Design & Delivery Contribute to the technical design and architecture of scalable AI solutions. Evaluate AI technologies, frameworks, and third-party services, making recommendations based on technical and business requirements. Participate in technical design reviews and support architectural decisions for complex AI initiatives. Help implement responsible AI, model governance, and production machine learning practices. Work with technical and product stakeholders to translate business requirements into practical AI solutions. Provide technical insights and feasibility assessments to support product and engineering decisions. Technical Expertise & Execution Solve complex AI engineering challenges and provide technical guidance to other engineers. Develop proof-of-concepts for emerging AI technologies and assess their suitability for production use. Build and deliver production-ready AI and Generative AI solutions using LLMs, RAG architectures, agents, and responsible AI practices. Implement and maintain retrieval pipelines using embeddings, vector databases, hybrid search methods, and effective chunking strategies. Design evaluation approaches to assess model quality, retrieval performance, reliability, and business outcomes. Use AI coding assistants such as Cursor, GitHub Copilot, and Claude Code to accelerate development while maintaining ownership of code quality and outcomes. Diagnose and resolve performance, scalability, reliability, and cost issues within production AI systems. Engineering Standards & Enablement Contribute to engineering best practices, coding standards, and quality benchmarks for AI development. Develop and improve internal AI tooling, including shared libraries, SDKs, and reusable components for RAG, tracing, prompt management, and evaluation. Conduct code reviews and support the development of less-experienced engineers through mentoring and knowledge sharing. Contribute to internal AI enablement activities, technical documentation, demonstrations, and best-practice guidance. Promote maintainable, observable, secure, and well-tested approaches to AI engineering. Cross-functional Collaboration Collaborate closely with Product using a working-backwards approach, contributing to technical designs, breaking down work, and delivering iteratively. Work with Security, Legal, and Data teams to apply AI policies and address privacy, PII protection, security, and regulatory requirements. Communicate technical decisions, risks, trade-offs, and progress clearly to technical and non-technical stakeholders. Partner with software, platform, and data engineers to integrate AI capabilities into wider products and services. Skills, Knowledge and Expertise Must Have 5+ years of software engineering experience, including 2+ years building production AI, Generative AI, or RAG systems. Strong experience designing, building, deploying, and maintaining AI systems in production environments. Demonstrated ability to make sound technical decisions and deliver solutions with measurable business impact. Strong knowledge of LLMs, RAG, agentic workflows, prompt engineering, embeddings, vector databases, and hybrid search techniques. Hands-on experience with leading LLM providers, such as Anthropic and OpenAI, including model selection, evaluation, and optimisation. Advanced Python development skills and experience using AI coding assistants such as Cursor, GitHub Copilot, or Claude Code. Production experience with AWS cloud services and containerised environments, including Kubernetes. Experience building reliable APIs, services, and integration patterns for AI-enabled applications. Strong data engineering capabilities, including dataset creation, ETL development, data quality management, and metrics definition. Solid understanding of machine learning fundamentals, experimentation methodologies, and model performance optimisation. Strong technical communication skills and the ability to collaborate effectively across engineering, product, data, security, and legal teams. Experience applying software engineering practices such as automated testing, version control, continuous integration, observability, and documentation. Nice to Have Experience with model fine-tuning, RLHF, or custom training approaches. Familiarity with MLOps platforms and experiment-tracking tools. Experience with infrastructure as code, such as Terraform or CloudFormation. Experience with LLM evaluation, tracing, prompt management, or AI observability platforms. Background in NLP research or contributions to open-source AI or machine learning projects.
26/06/2026
Full time
Senior AI Engineer - Permanent - London/Hybrid Permanent Hybrid in Central London Competitive Salary Key Responsibilities Technical Design & Delivery Contribute to the technical design and architecture of scalable AI solutions. Evaluate AI technologies, frameworks, and third-party services, making recommendations based on technical and business requirements. Participate in technical design reviews and support architectural decisions for complex AI initiatives. Help implement responsible AI, model governance, and production machine learning practices. Work with technical and product stakeholders to translate business requirements into practical AI solutions. Provide technical insights and feasibility assessments to support product and engineering decisions. Technical Expertise & Execution Solve complex AI engineering challenges and provide technical guidance to other engineers. Develop proof-of-concepts for emerging AI technologies and assess their suitability for production use. Build and deliver production-ready AI and Generative AI solutions using LLMs, RAG architectures, agents, and responsible AI practices. Implement and maintain retrieval pipelines using embeddings, vector databases, hybrid search methods, and effective chunking strategies. Design evaluation approaches to assess model quality, retrieval performance, reliability, and business outcomes. Use AI coding assistants such as Cursor, GitHub Copilot, and Claude Code to accelerate development while maintaining ownership of code quality and outcomes. Diagnose and resolve performance, scalability, reliability, and cost issues within production AI systems. Engineering Standards & Enablement Contribute to engineering best practices, coding standards, and quality benchmarks for AI development. Develop and improve internal AI tooling, including shared libraries, SDKs, and reusable components for RAG, tracing, prompt management, and evaluation. Conduct code reviews and support the development of less-experienced engineers through mentoring and knowledge sharing. Contribute to internal AI enablement activities, technical documentation, demonstrations, and best-practice guidance. Promote maintainable, observable, secure, and well-tested approaches to AI engineering. Cross-functional Collaboration Collaborate closely with Product using a working-backwards approach, contributing to technical designs, breaking down work, and delivering iteratively. Work with Security, Legal, and Data teams to apply AI policies and address privacy, PII protection, security, and regulatory requirements. Communicate technical decisions, risks, trade-offs, and progress clearly to technical and non-technical stakeholders. Partner with software, platform, and data engineers to integrate AI capabilities into wider products and services. Skills, Knowledge and Expertise Must Have 5+ years of software engineering experience, including 2+ years building production AI, Generative AI, or RAG systems. Strong experience designing, building, deploying, and maintaining AI systems in production environments. Demonstrated ability to make sound technical decisions and deliver solutions with measurable business impact. Strong knowledge of LLMs, RAG, agentic workflows, prompt engineering, embeddings, vector databases, and hybrid search techniques. Hands-on experience with leading LLM providers, such as Anthropic and OpenAI, including model selection, evaluation, and optimisation. Advanced Python development skills and experience using AI coding assistants such as Cursor, GitHub Copilot, or Claude Code. Production experience with AWS cloud services and containerised environments, including Kubernetes. Experience building reliable APIs, services, and integration patterns for AI-enabled applications. Strong data engineering capabilities, including dataset creation, ETL development, data quality management, and metrics definition. Solid understanding of machine learning fundamentals, experimentation methodologies, and model performance optimisation. Strong technical communication skills and the ability to collaborate effectively across engineering, product, data, security, and legal teams. Experience applying software engineering practices such as automated testing, version control, continuous integration, observability, and documentation. Nice to Have Experience with model fine-tuning, RLHF, or custom training approaches. Familiarity with MLOps platforms and experiment-tracking tools. Experience with infrastructure as code, such as Terraform or CloudFormation. Experience with LLM evaluation, tracing, prompt management, or AI observability platforms. Background in NLP research or contributions to open-source AI or machine learning projects.
DV Cleared Senior AI Engineer Location: London (Hybrid) Contract Type: Contract Day rate: 700 Outside Clearance Required: Active UK DV Clearance (Mandatory) The Opportunity We are partnering with a premier UK deep-tech venture that sits at the cutting edge of AI, robotics, and national security. They build advanced software frameworks that fuse complex, multi-modal data streams (sensor feeds, telemetry, imagery, and text) to enable Real Time decision-making in high-stakes, mission-critical environments. With multiple positions open due to rapid growth, they are looking for production-focused AI Engineers who want high ownership, fast-paced delivery, and the chance to deploy agentic systems that protect critical national infrastructure and save lives. Key Responsibilities Architect & Build: Design, optimize, and scale robust multi-agent AI pipelines and orchestration frameworks. Model Integration: Integrate LLMs and vision-language models (VLMs) into workflows optimized for reasoning, search, and autonomous task execution. Secure Deployment: Package and deploy AI systems into highly secure, cloud, on-premises, and air-gapped environments. Production MLOps: Build end-to-end data ingestion and inference pipelines with a heavy focus on system reliability over raw speed to market. Observability & Evaluation: Implement monitoring tooling to track agent behavior, model performance, drift, and unexpected failure modes. Technical Leadership: Serve as a subject matter expert for agentic AI, helping establish engineering patterns and mentoring junior developers. Technical Requirements Must-Have: Active UK DV Clearance. (Applications without this cannot be considered). Commercial AI Delivery: A proven track record of shipping multi-agent or agentic AI frameworks into live production environments. Core Software Engineering: Exceptional Python skills alongside hands-on experience with LLM orchestration tools (eg, LangGraph, LangChain, Haystack, or similar). Modern DevOps: Strong experience with Docker, Git, and cloud infrastructure. Secure Architecture: Solid comprehension of secure-by-design principles and deployment patterns for sovereign clouds or disconnected networks. Great-to-Have: Experience with edge computing, offline AI deployments, or local model execution. Familiarity with Kubernetes (EKS/OpenShift) for container management and application monitoring. Knowledge of advanced agent orchestration protocols (eg, A2A communication) and Model Context Protocols (MCPs). Familiarity with secure development frameworks (OWASP, NIST, ISO 27001). Background working in Defence, GovTech, aerospace, or similarly regulated sectors.
26/06/2026
Contractor
DV Cleared Senior AI Engineer Location: London (Hybrid) Contract Type: Contract Day rate: 700 Outside Clearance Required: Active UK DV Clearance (Mandatory) The Opportunity We are partnering with a premier UK deep-tech venture that sits at the cutting edge of AI, robotics, and national security. They build advanced software frameworks that fuse complex, multi-modal data streams (sensor feeds, telemetry, imagery, and text) to enable Real Time decision-making in high-stakes, mission-critical environments. With multiple positions open due to rapid growth, they are looking for production-focused AI Engineers who want high ownership, fast-paced delivery, and the chance to deploy agentic systems that protect critical national infrastructure and save lives. Key Responsibilities Architect & Build: Design, optimize, and scale robust multi-agent AI pipelines and orchestration frameworks. Model Integration: Integrate LLMs and vision-language models (VLMs) into workflows optimized for reasoning, search, and autonomous task execution. Secure Deployment: Package and deploy AI systems into highly secure, cloud, on-premises, and air-gapped environments. Production MLOps: Build end-to-end data ingestion and inference pipelines with a heavy focus on system reliability over raw speed to market. Observability & Evaluation: Implement monitoring tooling to track agent behavior, model performance, drift, and unexpected failure modes. Technical Leadership: Serve as a subject matter expert for agentic AI, helping establish engineering patterns and mentoring junior developers. Technical Requirements Must-Have: Active UK DV Clearance. (Applications without this cannot be considered). Commercial AI Delivery: A proven track record of shipping multi-agent or agentic AI frameworks into live production environments. Core Software Engineering: Exceptional Python skills alongside hands-on experience with LLM orchestration tools (eg, LangGraph, LangChain, Haystack, or similar). Modern DevOps: Strong experience with Docker, Git, and cloud infrastructure. Secure Architecture: Solid comprehension of secure-by-design principles and deployment patterns for sovereign clouds or disconnected networks. Great-to-Have: Experience with edge computing, offline AI deployments, or local model execution. Familiarity with Kubernetes (EKS/OpenShift) for container management and application monitoring. Knowledge of advanced agent orchestration protocols (eg, A2A communication) and Model Context Protocols (MCPs). Familiarity with secure development frameworks (OWASP, NIST, ISO 27001). Background working in Defence, GovTech, aerospace, or similarly regulated sectors.
Salary £42,630 - £46,246, dependent on experience and made up of a base salary of £35,134 - £38,750, a concessionary payment of £2,758, and a skills payment of up to £4,738 (assessed at interview and offered from day one). You will also receive a one-off recruitment bonus of £2,000 (£1,000 on arrival and £1,000 on successful completion of probation). Flexible Working We recognise the importance of a healthy work life balance and offer full time, part time, and compressed hours. Due to the nature of the work, hybrid working may be more limited; however, some home working options may be available depending on business requirements. About GCHQ GCHQ is an intelligence, cyber and security agency with a mission to keep the UK safe. We use cutting edge technology, ingenuity, and partnerships to identify, analyse and disrupt threats. Working with our intelligence partners MI5 and MI6, we protect the UK from terrorism, cyber attacks, and espionage. At GCHQ, you'll do varied and fascinating work in a supportive and inclusive environment that puts the emphasis on teamwork. The Role A typical day as a Software Engineer at GCHQ involves working both collaboratively and independently to develop innovative solutions to complex, real world mission challenges. As part of an Agile, multidisciplinary team, you'll contribute to a culture of continuous learning and adaption. Teams experiment with new ideas, explore different technical approaches and tackle difficult problems that often require fresh thinking. Collaboration with analysts and technical specialists across multiple missions is central to shaping solutions that meet operational needs. Day to day work may include team check ins and planning sessions, reviewing and raising pull requests, and applying a range of engineering practices such as pair programming, mobbing, or focused individual development. You might also spend time researching and analysing web or mobile technologies, designing, documenting and implementing software solutions, and delivering software for mission requirements. You'll also support existing solutions throughout their lifecycle, all contributing to steady progress and well crafted outcomes. About You You'll bring a real aptitude for learning and problem solving, with a genuine interest in technology and trying new approaches. You enjoy developing ideas, exploring technical options and working with others to solve challenges. You will have practical experience in a software development environment gained through a previous role or an industrial placement. You're comfortable using at least one modern programming language or framework and have a good understanding of core software engineering practices. You'll be curious about cloud technologies, and any familiarity with AWS, Azure or GCP would be beneficial. You may have some experience with Agile or DevOps ways of working, CI/CD, automation or infrastructure as code, and you're keen to build confidence in areas like cloud security or vulnerability awareness. A basic understanding of Linux or Windows is useful, along with a willingness to learn more as part of the role. You'll work well in development teams, switching between independent tasks and collaborative work, and you're happy contributing across teams when needed. You can prioritise effectively, adapt to change and stay focused when things get challenging. You communicate clearly, enjoy sharing ideas and are comfortable engaging with a range of customers and technical colleagues. Training and Development At GCHQ, we embrace a growth mindset and are committed to your development. You'll follow a blend of in house learning from our experts, external courses where helpful, and plenty of on the job experience. From day one, you'll have access to mentors and subject matter experts who will support you in building a development and career plan that works for you. We encourage you to dedicate time to continual professional development through formal courses and practical experimentation, supported by the innovation time available to you. You'll have access to books, online learning platforms, conferences and practical project work supported by experienced colleagues, along with funding towards formal qualifications. Training covers a broad range of areas, including Front End Design, RF Software Engineering, Site Reliability Engineering, Data Engineering, Solution Architecture, MLOps, UX, Agile, Cloud Engineering and Security. You'll also have access to courses including AWS certification, Scrum Master training, microservices, engineering patterns, Linux, user experience and leadership skills. Subscriptions to platforms like Cloud Academy, Pluralsight or O'Reilly are also available. Rewards and Benefits 25 days' annual leave, rising automatically to 30 days after 5 years' service, plus an additional 10.5 days of public and privilege holidays opportunities to be recognised through our employee performance scheme an interest free season ticket loan a cycle to work scheme facilities such as a gym, restaurant, and on site coffee bars (at some locations) paid parental and adoption leave Diversity and Inclusion At GCHQ, diversity and inclusion are critical to our mission. To protect the UK, we need a workforce that truly reflects the society we serve. This includes diversity in every sense of the word: people of 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 individuals from groups that are currently under represented in our workforce, such as women, people from ethnic minority backgrounds, people with disabilities and those from low socio economic backgrounds. GCHQ is proud to have achieved Leader status within the Department for Work and Pensions' Disability Confident scheme. The scheme encourages employers to think differently about disability and take action to improve how they recruit, retain and develop disabled people. As a Disability Confident organisation, we aim to ensure that a fair and proportionate number of disabled applicants who best meet the essential criteria for this position, assessed at sift, are offered an interview, if it is practical for us to do so. This is known as the Offer of Interview. Minimum Criteria Demonstrate a strong motivation to learn and adapt to Agile ways of working. Demonstrate an ability to develop software features. Demonstrate experience of working as a Software Engineer in a software engineering environment. This could include an industry placement. Requirements The role requires the highest security clearance, known as Developed Vetting (DV). The role is based in Manchester or Samlesbury, and you'll need to live within a commutable distance. You must be a British citizen or hold dual British nationality.
26/06/2026
Full time
Salary £42,630 - £46,246, dependent on experience and made up of a base salary of £35,134 - £38,750, a concessionary payment of £2,758, and a skills payment of up to £4,738 (assessed at interview and offered from day one). You will also receive a one-off recruitment bonus of £2,000 (£1,000 on arrival and £1,000 on successful completion of probation). Flexible Working We recognise the importance of a healthy work life balance and offer full time, part time, and compressed hours. Due to the nature of the work, hybrid working may be more limited; however, some home working options may be available depending on business requirements. About GCHQ GCHQ is an intelligence, cyber and security agency with a mission to keep the UK safe. We use cutting edge technology, ingenuity, and partnerships to identify, analyse and disrupt threats. Working with our intelligence partners MI5 and MI6, we protect the UK from terrorism, cyber attacks, and espionage. At GCHQ, you'll do varied and fascinating work in a supportive and inclusive environment that puts the emphasis on teamwork. The Role A typical day as a Software Engineer at GCHQ involves working both collaboratively and independently to develop innovative solutions to complex, real world mission challenges. As part of an Agile, multidisciplinary team, you'll contribute to a culture of continuous learning and adaption. Teams experiment with new ideas, explore different technical approaches and tackle difficult problems that often require fresh thinking. Collaboration with analysts and technical specialists across multiple missions is central to shaping solutions that meet operational needs. Day to day work may include team check ins and planning sessions, reviewing and raising pull requests, and applying a range of engineering practices such as pair programming, mobbing, or focused individual development. You might also spend time researching and analysing web or mobile technologies, designing, documenting and implementing software solutions, and delivering software for mission requirements. You'll also support existing solutions throughout their lifecycle, all contributing to steady progress and well crafted outcomes. About You You'll bring a real aptitude for learning and problem solving, with a genuine interest in technology and trying new approaches. You enjoy developing ideas, exploring technical options and working with others to solve challenges. You will have practical experience in a software development environment gained through a previous role or an industrial placement. You're comfortable using at least one modern programming language or framework and have a good understanding of core software engineering practices. You'll be curious about cloud technologies, and any familiarity with AWS, Azure or GCP would be beneficial. You may have some experience with Agile or DevOps ways of working, CI/CD, automation or infrastructure as code, and you're keen to build confidence in areas like cloud security or vulnerability awareness. A basic understanding of Linux or Windows is useful, along with a willingness to learn more as part of the role. You'll work well in development teams, switching between independent tasks and collaborative work, and you're happy contributing across teams when needed. You can prioritise effectively, adapt to change and stay focused when things get challenging. You communicate clearly, enjoy sharing ideas and are comfortable engaging with a range of customers and technical colleagues. Training and Development At GCHQ, we embrace a growth mindset and are committed to your development. You'll follow a blend of in house learning from our experts, external courses where helpful, and plenty of on the job experience. From day one, you'll have access to mentors and subject matter experts who will support you in building a development and career plan that works for you. We encourage you to dedicate time to continual professional development through formal courses and practical experimentation, supported by the innovation time available to you. You'll have access to books, online learning platforms, conferences and practical project work supported by experienced colleagues, along with funding towards formal qualifications. Training covers a broad range of areas, including Front End Design, RF Software Engineering, Site Reliability Engineering, Data Engineering, Solution Architecture, MLOps, UX, Agile, Cloud Engineering and Security. You'll also have access to courses including AWS certification, Scrum Master training, microservices, engineering patterns, Linux, user experience and leadership skills. Subscriptions to platforms like Cloud Academy, Pluralsight or O'Reilly are also available. Rewards and Benefits 25 days' annual leave, rising automatically to 30 days after 5 years' service, plus an additional 10.5 days of public and privilege holidays opportunities to be recognised through our employee performance scheme an interest free season ticket loan a cycle to work scheme facilities such as a gym, restaurant, and on site coffee bars (at some locations) paid parental and adoption leave Diversity and Inclusion At GCHQ, diversity and inclusion are critical to our mission. To protect the UK, we need a workforce that truly reflects the society we serve. This includes diversity in every sense of the word: people of 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 individuals from groups that are currently under represented in our workforce, such as women, people from ethnic minority backgrounds, people with disabilities and those from low socio economic backgrounds. GCHQ is proud to have achieved Leader status within the Department for Work and Pensions' Disability Confident scheme. The scheme encourages employers to think differently about disability and take action to improve how they recruit, retain and develop disabled people. As a Disability Confident organisation, we aim to ensure that a fair and proportionate number of disabled applicants who best meet the essential criteria for this position, assessed at sift, are offered an interview, if it is practical for us to do so. This is known as the Offer of Interview. Minimum Criteria Demonstrate a strong motivation to learn and adapt to Agile ways of working. Demonstrate an ability to develop software features. Demonstrate experience of working as a Software Engineer in a software engineering environment. This could include an industry placement. Requirements The role requires the highest security clearance, known as Developed Vetting (DV). The role is based in Manchester or Samlesbury, and you'll need to live within a commutable distance. You must be a British citizen or hold dual British nationality.
As a Software Engineer specializing in AI systems, you will play a key role in designing and implementing production grade software solutions that leverage cutting edge machine learning techniques, including large language models (LLMs), natural language processing systems (NLP), and AI agents. Your primary focus will be building scalable, efficient, and maintainable backend systems using Node.js and Python, while also integrating machine learning workflows and AI driven applications. You will work closely with data scientists, machine learning engineers, and other stakeholders to develop robust platforms capable of supporting advanced AI capabilities. Skills and Competencies 3+ years of experience in backend software development with a focus on Node.js, building scalable and production grade systems Hands on experience with AI applications, including LLM implementations, retrieval augmented generation, prompt optimization, and fine tuning methodologies Proven ability to optimize systems for latency, cost, and reliability, and to take AI agents from research to production Strong knowledge of cloud platforms (e.g., AWS, GCP, Azure), containerization technologies (e.g., Docker, ECS, Kubernetes), and MLOps practices Proficiency in databases (e.g., PostgreSQL, MongoDB) and caching systems (e.g., Redis, Memcached) for scalable data storage and retrieval Familiarity with Python for collaborating on machine learning workflows and integrating Python based AI tools is preferred Excellent problem solving skills, with the ability to navigate ambiguity and deliver impactful solutions aligned with business goals Effective communication and collaboration skills, with demonstrated experience working across cross functional teams Education Bachelor's degree or higher in Computer Science, Software Engineering, or a related field. Responsibilities Design and implement AI driven backend systems using Node.js, creating APIs and services to support applications such as NLP, search, recommendation systems, and AI agents. Build and integrate large language model (LLM) applications and AI agents using techniques such as retrieval augmented generation, prompt optimization, fine tuning, and reinforcement learning. Develop end to end pipelines for data ingestion, feature engineering, model inference (batch and real time), and integration of AI driven workflows into production systems. Collaborate with data scientists and machine learning engineers to ensure seamless integration of machine learning practices in Gen AI. Optimize backend systems for latency, scalability, and cost, applying caching, load balancing, and other performance techniques to support high volume inference workloads. Advocate for and implement MLOps best practices, including monitoring, logging, tracing, automated retraining, and model/prompt versioning to ensure robust and reliable AI systems. Build reusable platforms or frameworks that streamline the deployment and monitoring of AI agents and machine learning models. Lead the implementation of autonomous agents capable of multi step reasoning, decision making, and tool use in production environments. Participate in design reviews, write high quality code, and contribute to documentation to ensure team wide efficiency and maintainability. Mentor junior engineers and collaborate across disciplines to drive impactful solutions while aligning system design with business outcomes. Moody's is an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, national origin, disability, protected veteran status, sexual orientation, gender expression, gender identity or any other characteristic protected by law. Candidates for Moody's Corporation may be asked to disclose securities holdings pursuant to Moody's Policy for Securities Trading and the requirements of the position. Employment is contingent upon compliance with the Policy, including remediation of positions in those holdings as necessary.
26/06/2026
Full time
As a Software Engineer specializing in AI systems, you will play a key role in designing and implementing production grade software solutions that leverage cutting edge machine learning techniques, including large language models (LLMs), natural language processing systems (NLP), and AI agents. Your primary focus will be building scalable, efficient, and maintainable backend systems using Node.js and Python, while also integrating machine learning workflows and AI driven applications. You will work closely with data scientists, machine learning engineers, and other stakeholders to develop robust platforms capable of supporting advanced AI capabilities. Skills and Competencies 3+ years of experience in backend software development with a focus on Node.js, building scalable and production grade systems Hands on experience with AI applications, including LLM implementations, retrieval augmented generation, prompt optimization, and fine tuning methodologies Proven ability to optimize systems for latency, cost, and reliability, and to take AI agents from research to production Strong knowledge of cloud platforms (e.g., AWS, GCP, Azure), containerization technologies (e.g., Docker, ECS, Kubernetes), and MLOps practices Proficiency in databases (e.g., PostgreSQL, MongoDB) and caching systems (e.g., Redis, Memcached) for scalable data storage and retrieval Familiarity with Python for collaborating on machine learning workflows and integrating Python based AI tools is preferred Excellent problem solving skills, with the ability to navigate ambiguity and deliver impactful solutions aligned with business goals Effective communication and collaboration skills, with demonstrated experience working across cross functional teams Education Bachelor's degree or higher in Computer Science, Software Engineering, or a related field. Responsibilities Design and implement AI driven backend systems using Node.js, creating APIs and services to support applications such as NLP, search, recommendation systems, and AI agents. Build and integrate large language model (LLM) applications and AI agents using techniques such as retrieval augmented generation, prompt optimization, fine tuning, and reinforcement learning. Develop end to end pipelines for data ingestion, feature engineering, model inference (batch and real time), and integration of AI driven workflows into production systems. Collaborate with data scientists and machine learning engineers to ensure seamless integration of machine learning practices in Gen AI. Optimize backend systems for latency, scalability, and cost, applying caching, load balancing, and other performance techniques to support high volume inference workloads. Advocate for and implement MLOps best practices, including monitoring, logging, tracing, automated retraining, and model/prompt versioning to ensure robust and reliable AI systems. Build reusable platforms or frameworks that streamline the deployment and monitoring of AI agents and machine learning models. Lead the implementation of autonomous agents capable of multi step reasoning, decision making, and tool use in production environments. Participate in design reviews, write high quality code, and contribute to documentation to ensure team wide efficiency and maintainability. Mentor junior engineers and collaborate across disciplines to drive impactful solutions while aligning system design with business outcomes. Moody's is an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, national origin, disability, protected veteran status, sexual orientation, gender expression, gender identity or any other characteristic protected by law. Candidates for Moody's Corporation may be asked to disclose securities holdings pursuant to Moody's Policy for Securities Trading and the requirements of the position. Employment is contingent upon compliance with the Policy, including remediation of positions in those holdings as necessary.
