37 jobs found

A dynamic AI startup in London is seeking a Founding Systems Engineer to lead their ML Infrastructure team. This role involves driving DevOps and MLOps across R&D and production environments, focusing on automation and cross-functional collaboration. Ideal candidates will have experience with MLOps tooling, cloud platforms, and excellent engineering skills. You'll work with a world-class team to tackle challenging infrastructure problems and help shape the company's engineering culture. Founding equity offered.

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.

About aion Aion is the enterprise AI platform, a full-stack solution for building, fine-tuning, and deploying AI at scale. Whether an organization is modernizing internal operations, launching AI-powered products, or transforming customer experiences, Aion takes them from concept to production on a single, unified platform. We work differently than most AI companies: our teams deploy alongside our customers, turning production-ready AI into real business outcomes in weeks, not quarters. We're a fast-growing, VC backed startup led by founders with a track record of successful exits. With teams across the US, UK, and India, we're building the next generation of enterprise AI and we're looking for exceptional people to help us scale. Who You Are You're a customer focused AI consultant and software engineer who enjoys solving complex business problems using cutting edge AI technologies. You have experience working directly with enterprise customers, understanding their business challenges, and designing scalable AI solutions that deliver measurable business outcomes. You combine strong technical expertise with exceptional consulting skills. You're comfortable translating business requirements into solution architectures, collaborating with engineering teams to deliver production ready AI applications, and guiding customers through every stage of their AI transformation journey. You're product mindful and understand that successful AI adoption is about more than technology. It requires strategic thinking, customer empathy, technical leadership, and the ability to align AI capabilities with business objectives. You thrive in customer facing environments, enjoy working across multiple industries, and are excited to help organizations unlock the full potential of enterprise AI. What You'll Do Customer Discovery & AI Consulting Partner with enterprise customers to understand their business challenges, workflows, and AI transformation goals. Conduct discovery workshops, technical assessments, and solution design sessions to identify high impact AI opportunities. Advise customers on AI strategy, implementation roadmaps, and best practices for enterprise AI adoption. Translate complex business requirements into scalable AI solutions aligned with customer objectives. Solution Architecture Design end to end AI solution architectures using Aion's enterprise AI platform. Create scalable, secure, and production ready architectures for AI applications, intelligent agents, automation workflows, and enterprise integrations. Define technical solution blueprints covering infrastructure, data flows, APIs, security, and deployment strategies. Collaborate closely with engineering teams to ensure successful implementation of customer solutions. Implementation & Delivery Lead technical solution delivery from proof of concept through production deployment. Work alongside customers during implementation, ensuring successful integration with existing enterprise systems. Support solution validation, performance optimization, testing, and production readiness. Resolve technical challenges and recommend architecture improvements throughout project execution. Cross functional Collaboration Partner with Product, Engineering, AI, Customer Success, and Sales teams to continuously improve Aion's platform and customer experience. Provide customer feedback that influences product roadmap and platform capabilities. Support technical demonstrations, solution workshops, RFP responses, and executive presentations. Develop reusable architecture patterns, reference implementations, and best practices for enterprise AI deployments. Thought Leadership Stay current with advancements in AI, Large Language Models, agentic AI, cloud infrastructure, and enterprise software. Represent Aion at customer meetings, industry events, and technical workshops. Contribute to solution playbooks, architecture documentation, and technical enablement materials. Help establish Aion as a trusted advisor in enterprise AI transformation. Technical Skills & Experience 5+ years of experience in Solutions Architecture, Technical Consulting, Enterprise Architecture, or Software Engineering. Experience designing and delivering enterprise software, cloud, or AI solutions for customers. Strong understanding of Large Language Models, Generative AI, Retrieval Augmented Generation (RAG), AI agents, and enterprise AI architectures. Experience with cloud platforms including AWS, Azure, or Google Cloud Platform. Understanding of APIs, microservices, distributed systems, and enterprise integration patterns. Experience designing secure, scalable, and highly available enterprise solutions. Familiarity with Kubernetes, Docker, cloud native technologies, and modern application architectures. Ability to communicate complex technical concepts to both technical and non technical stakeholders. Experience working with cross functional teams across engineering, product, sales, and customer success. Strong presentation, documentation, and stakeholder management skills. Bonus/ Good to Have Enterprise AI: Experience implementing enterprise AI platforms, intelligent automation, AI copilots, multi agent systems, or AI workflow orchestration. Industry Consulting: Experience working with customers across financial services, healthcare, manufacturing, retail, public sector, or other enterprise industries. Cloud & Infrastructure: Hands on experience with cloud architecture, Infrastructure as Code, DevOps, MLOps, or enterprise platform engineering. Pre sales & Customer Success: Experience supporting enterprise sales cycles, solution demonstrations, technical workshops, or proof of concept engagements. Enterprise Integrations: Experience integrating AI solutions with enterprise applications, CRMs, ERPs, productivity suites, and business systems. Preferred Attributes: Founder-level ownership and bias for action. Strong strategic thinking and ability to connect technical decisions to business impact. Excellent communication and mentoring skills. Thrives in ambiguity, fast paced environments, and early stage startup culture. Why Join aion? Work directly with high pedigree founders shaping technical and product strategy. Build infrastructure powering the future of AI compute globally. Significant ownership and impact with equity reflective of your contributions. Competitive compensation, flexible work options, and wellness benefits

Glassbox's mission is to empower enterprises to shape trusted, frictionless digital experiences. Glassbox is a leading force in shaping digital experiences. It helps organizations uncover digital issues, boost conversion rates, enhance accessibility, prevent fraud, and more. Leveraging AI-driven customer intelligence, Glassbox enables enterprises to deliver secure, proactive, and preventative digital experiences. Its solutions are trusted by highly regulated organizations, including SoFi, Cal, and many others. We are growing and have been recognized by G2 as one of 2024's Top 50 Software Companies in the world. Glassbox is looking for a DevOps Engineer to join our global team. What You Will do? You will work with cutting-edge technologies and tackle a wide range of challenges in building a scalable, globally distributed infrastructure. In this role, you will: Work with a diverse set of technologies, simplifying complex solutions. Collaborate closely with multiple teams across the organization. Be part of a team responsible for designing, optimizing, and maintaining a high-scale production environment that handles massive traffic loads with high complexity. Architect, deploy, and maintain robust and scalable cloud infrastructures on AWS and Azure. Develop and optimize CI/CD pipelines to support automated deployment, testing, and scaling across multiple environments. Implement and manage monitoring, logging, and alerting solutions across cloud platforms to ensure application health and performance. Provide advanced troubleshooting and resolution for infrastructure issues in production, development, and testing environments. What You Will Need? 4+ years of experience in a DevOps or related engineering role, with a strong background in AWS and cloud-native environments. Proven ability to design, manage, and maintain high-scale production systems, ensuring reliability, performance, and scalability. Deep expertise in cloud technologies and application security, with a strong focus on best practices for securing resilient, scalable, and cost-efficient architectures. Extensive experience with containerization and orchestration technologies, including Docker, Kubernetes, and Helm. Proficiency in automation tools such as Terraform, and hands on experience with CI/CD pipelines using tools like Jenkins. Strong knowledge of monitoring and logging tools (e.g., Prometheus, Grafana, Loki) to ensure system health, optimize performance, and proactively detect issues. Proficiency in scripting languages (e.g., Node.js, Bash) to automate workflows and enhance operational efficiency. Excellent communication, collaboration, and documentation skills, with a proactive approach to problem solving. Passionate about learning new technologies and tackling complex challenges in a fast paced environment. Hands on experience managing big data infrastructure, optimizing performance and scalability for data intensive applications. Preferred Proficiency in database technologies, including Cassandra, Elasticsearch, ClickHouse, and PostgreSQL HA. Expertise in Kafka cluster administration, including cross region replication and high availability configurations. Experience with MLOps workflows and infrastructure, including model deployment, monitoring, and scaling in production environments. At Glassbox, we value curiosity, ownership, and a constant drive to learn and improve, no matter the gender, nationality, religion, or background. We believe diverse perspectives make us better, and that potential matters just as much as experience, and encourage people of all shapes and sizes to apply. If this role excites you and you're motivated to make an impact - we'd love to hear from you, even if you don't meet every listed qualification.

We are Permutable AI - a London based market intelligence company transforming how global institutions understand markets. Founded in 2020 by former Merrill Lynch and Citibank trader Wilson Chan, we were built on a simple realisation: the world's markets now move faster than legacy intelligence systems can interpret. Our purpose is to redefine how financial institutions process information by delivering real-time, explainable AI that turns billions of global data points into immediate, actionable insight. Our platform powers energy, commodities, macro and multi-asset teams with intelligence that is fast, transparent and institutionally robust - bringing clarity to markets where speed and understanding matter most. Our vision is to create the most advanced real-time intelligence system in the world, capable of understanding global events the moment they unfold, with full transparency and traceability. By combining multi-LLM architectures with deep engineering expertise, we are setting the new benchmark for how capital markets integrate sentiment, narrative and macro interpretation into everyday decision-making. Senior DevOps Engineer As we embark on an exciting phase of growth, we are looking to bring on a talented Sr DevOps Engineer. You will be joining a small team where research and engineering doesn't sit on a shelf - it powers live trading decisions. You will be supporting customer-facing rollouts with Product and Commercial teams, ensuring production reliability. Additionally, you will help improve engineering processes, observability, and system resilience as we scale. Behind every line of code and every dataset, there's a team of curious, driven people who bring ideas to life. At Permutable AI, ambitious engineers can do their best work without getting lost in a corporate machine. Experience and qualities we'd like you to have: 4+ years' relevant experience in a similar DevOps Engineer focused role expert AWS, strong CI/CD and IaC and strong experience building, deploying and operating reliable, scalable, end-to-end production APIs and data pipelines for external clients strong understanding of cloud infrastructure, observability, monitoring, incident response, and operational best practices relevant technologies (we use): AWS incl. S3, ECS, API Gateway, Batch, Redshift, Airflow, GitHub Actions, Docker, Pulumi, Python, Javascript/react high ownership mentality who can work across the stack with a primary responsibility for DevOps reliability demonstrated experience working in start-up/scale-up environment(s) similar experience in data, AI, market data, fintech or other institutional/enterprise-facing API products excellent communication and pragmatic, methodical decision making skills happy to stay hands on while helping the platform function operate more effectively self starter with a passion for building innovative products and leading small teams ability to balance speed with robustness, and challenge/push back when necessary Bonus points: experience with streaming architecture notable passion projects understanding of machine learning and/or experience building out MLOPS on top of DevOps experience with scaling LLM/agentic products Working for us: At Permutable AI, we believe that innovation thrives in an environment where curiosity meets collaboration. Our culture is built on trust, transparency, and a shared passion for solving complex challenges in global markets. We empower our team to take ownership, experiment boldly, and learn continuously, knowing that every voice matters. Whether you're developing cutting-edge AI models, surfacing new market insights, or building relationships with our clients, you'll find the freedom to make a real impact - supported by a team that values diversity, inclusion, and mutual respect. Do you thrive in dynamic, innovative environments where your work can truly make a difference? If you're looking for your next role at one of the best AI startups to work for London, you might just be the talent we're seeking. Final bits: This role will be a full-time permanent position, offering hybrid/flexible working out of our London (Vauxhall) office. We offer a competitive salary, equity options, 28 days holiday allowance, your birthday off, paid bank holidays, pension, and quarterly team outings and regular socials. We are a people led business with a transparent, encouraging and friendly culture.

About Permutable Permutable is a technology company delivering real-time, AI-driven solutions for the financial sector. By combining advanced language models with deep financial expertise, our platform helps traders, hedge funds and investment professionals access timely market intelligence and make better-informed decisions. Our solutions are designed to reduce the time required for market analysis while improving the quality and depth of investment research. Trusted by leading financial institutions, we focus on creating practical, easy-to-implement tools that deliver tangible value. Based in London, Permutable is working to transform how financial professionals understand markets and use information in their decision-making. The opportunity We are looking for a Senior MLOps & Platform Engineer to help build and strengthen the technical foundations behind our AI-driven financial solutions. You will be responsible for designing, building and maintaining the software infrastructure that supports our large-scale machine-learning applications. Your work will directly influence the reliability, scalability and performance of the proprietary tools used by our clients. This is an opportunity to apply your engineering experience to complex, meaningful problems at the intersection of artificial intelligence and financial markets. You will work closely with colleagues across the business, helping turn advanced technology into dependable products that deliver real value. The role is based in London and offers a hybrid working arrangement, with flexibility to work both from the office and remotely as needed. What you will do Design, build and maintain robust software infrastructure for large-scale machine-learning applications. Troubleshoot complex technical issues across software and infrastructure. Manage and optimise databases supporting AI-driven financial solutions. Improve programming workflows and system performance. Write efficient, scalable and well-optimised code. Support the reliability, scalability and performance of Permutable's proprietary tools. Work collaboratively with cross-functional teams to solve technical challenges. Contribute to the continued development of cloud, DevOps and CI/CD practices. What we are looking for Strong troubleshooting and problem-solving skills within complex technical systems. Experience in software development and infrastructure management. Strong programming skills and the ability to write optimised, scalable code. Hands-on experience with database design, management and optimisation. Familiarity with cloud platforms, DevOps practices and CI/CD pipelines. Experience with AI or MLOps frameworks would be an advantage. A bachelor's or master's degree in computer science, software engineering or a related field. Strong analytical thinking and the ability to work effectively across different teams. Why join Permutable Permutable combines the energy and pace of a growing start-up with a close-knit, ambitious and supportive team. You will have real ownership of your work, the freedom to influence technical decisions and the opportunity to see the direct impact of what you build. We value people who take initiative, share ideas and want to help shape both the platform and the company as we grow. We also make time to bring the team together through regular socials, company offsites and informal opportunities to connect beyond day-to-day work. This is a chance to join a strong start-up culture where your contribution will be visible, valued and genuinely important. Package Competitive base salary. Stock options. Flexible working days and hours. Hybrid working from London.

Here at Humanoid, we believe in a future where robots amplify human potential. That's why we've set out on a mission to build the world's most capable, commercially-scalable, and safe humanoid robots. We're bringing that mission to life with HMND 01 Alpha - our rapidly developed humanoid platform now running in real industrial pilots - and we're growing the team to take it even further. About The Role We're hiring a Senior Dev/MLOps Engineer to join our Data & Compute Platform team based in London. What You'll Do Own and manage the full lifecycle of both ML models and core infrastructure - from development and deployment to monitoring and continuous improvement. Build and maintain robust CI/CD pipelines for both software and ML workflows. Ensure reliability, scalability, observability, and security of production systems and ML infrastructure. Automate deployment, orchestration, and environment management using modern DevOps tooling. Collaborate closely with software engineers, data scientists, and product teams to bring ML-powered features to production. Proactively detect, troubleshoot, and resolve infrastructure and model performance issues. Stay up to date with industry best practices in DevOps, MLOps, and infrastructure engineering. Document infrastructure, workflows, and operational procedures clearly and thoroughly. What We're Looking For Proven experience in a senior-level DevOps, MLOps, or related infrastructure-focused engineering role. Strong proficiency in Python and familiarity with ML frameworks such as TensorFlow or PyTorch. Deep experience with cloud platforms (AWS, GCP, or Azure) and container orchestration tools (Docker, Kubernetes). Solid understanding of CI/CD systems (e.g., GitHub Actions, GitLab CI, ArgoCD) and infrastructure-as-code tools (e.g., Terraform, Helm). Familiarity with data engineering concepts such as ETL pipelines, data lakes, and large-scale batch/stream processing. Ability to design scalable, secure, and observable systems in fast-moving environments. Strong debugging and problem-solving skills across distributed systems. Excellent collaboration and communication skills, with experience working in cross-functional teams. Understanding of security and compliance best practices for both software and ML systems. What We Offer Meaningful time off to rest and recharge: 23 days of annual leave (accrued), 15 days of paid sick leave, and paid company holidays. Fully funded private healthcare for UK employees, with broad provider access, virtual and in person care, and strong mental health and serious illness support. Equity included-we believe builders should share in what they build. Pension scheme with a total 8% contribution (5% employee, 3% employer) on full earnings. Free daily breakfast, catered lunch, and snacks in office. Collaboration with top tier engineers, researchers, and product experts in AI and robotics. Freedom to influence the product and own key initiatives.

Responsibilities Design, build and deploy machine learning models to solve real-world business problems, including classification and optimisation use cases Develop and implement LLM-based applications, including prompt engineering, fine-tuning where appropriate, and orchestration of model/agent workflows via tools like LangChain. Build and maintain RAG, GRAPH pipelines, including document ingestion, embedding generation, vector search and retrieval strategies Evaluate model performance and trade-offs, balancing accuracy, explainability, cost and scalability Use Python as the primary language for data science and ML development. Write, optimise, and maintain SQL queries against relational databases to support analytics, feature generation, and model development. Collaborate on data pipelines and feature engineering to support model development and deployment Apply statistical and analytical techniques to inform insights and actions from the data. Work with structured and unstructured data, including text-heavy datasets used in LLM and RAG/GRAPH solutions Contribute to model deployment approaches with our DevOps team, including APIs, batch processes and integration with existing analytics platforms Work with cloud-based platforms and services (e.g. AWS, Azure, GCP) to support model training, deployment and scaling Use and evaluate modern AI tooling, frameworks and libraries (e.g. PyTorch, scikit-learn, LangChain/Graph/Smith, Vector databases, Graph Structures) Support experimentation and prototyping, helping move promising ideas into production-ready solutions Establish successful working relationships with business stakeholders and Domain leads to translate business problems into data science and AI solutions Partner with the Lead Data Scientist to identify new AI-driven opportunities and help shape Transform's AI capability and offerings Clearly communicate complex technical concepts, assumptions and outputs to non-technical audiences Document approaches, models and learnings to support knowledge sharing and reuse Qualifications Strong hands-on experience in data science and machine learning, with evidence of delivering production or near-production solutions Solid experience building models and applying statistical techniques using Python (experience with R is desirable but not essential) Practical experience with LLMs, including prompt engineering and building LLM-enabled applications Experience designing or working with RAG architectures, embeddings and vector search Strong understanding of machine learning fundamentals, including model evaluation, bias, overfitting and explainability Experience working with cloud services for data science and AI workloads Familiarity with MLOps or model deployment practices is desirable (e.g. versioning, monitoring, reproducibility) Strong problem-solving skills and a pragmatic mindset. Focused on delivering value, not just experimentation Ability to lead data science projects while collaborating effectively in multidisciplinary teams Excellent communication skills, with the ability to explain complex concepts simply Curiosity and enthusiasm for emerging AI technologies, with a desire to continuously learn and experiment

AI Solution Architects & Technical AI Leaders Scotland Hybrid We're supporting a major consulting and technology organization delivering enterprise AI and data transformation programmes across Financial Services. The focus is designing scalable AI architectures that move beyond proof of concept into secure, production-grade deployment across banking environments. Hiring across multiple levels, from Solution Architects through to senior technical leadership. What you'll be doing Designing AI and GenAI architecture strategies and roadmaps Building scalable AI/ML and Agentic AI platforms Working across LLMs, RAG, embeddings and semantic search Supporting AI deployment, governance and integration patterns Collaboration with engineering, data, DevOps and business teams Advising clients on AI platform capability and implementation strategy Environment Python LLMs, prompt engineering, fine-tuning, RAG LangChain, LangGraph, Agent frameworks Vector databases and semantic search MLOps and LLMOps AWS, Azure, GCP, Databricks Containerisation, Kubernetes and GPU infrastructure Requirements Experience designing enterprise AI or ML architectures Strong understanding of cloud and modern data platforms Exposure to scalable AI deployment and integration patterns Financial Services or regulated industry experience essential Strong stakeholder engagement and communication skills Open to candidates from Manager through to Associate Director level.

AI Solution Architects & Technical AI Leaders Manchester Hybrid We're supporting a major consulting and technology organisation delivering enterprise AI and data transformation programmes across Financial Services. The focus is designing scalable AI architectures that move beyond proof of concept into secure, production-grade deployment across banking environments. Hiring across multiple levels, from Solution Architects through to senior technical leadership. What you'll be doing Designing AI and GenAI architecture strategies and roadmaps Building scalable AI/ML and Agentic AI platforms Working across LLMs, RAG, embeddings and semantic search Supporting AI deployment, governance and integration patterns Collaborating with engineering, data, DevOps and business teams Advising clients on AI platform capability and implementation strategy Environment Python LLMs, prompt engineering, fine-tuning, RAG LangChain, LangGraph, Agent frameworks Vector databases and semantic search MLOps and LLMOps AWS, Azure, GCP, Databricks Containerisation, Kubernetes and GPU infrastructure Requirements Experience designing enterprise AI or ML architectures Strong understanding of cloud and modern data platforms Exposure to scalable AI deployment and integration patterns Financial Services or regulated industry experience essential Strong stakeholder engagement and communication skills Open to candidates from Manager through to Associate Director level.

AI Solution Architects & Technical AI Leaders London Hybrid We're supporting a major consulting and technology organisation delivering enterprise AI and data transformation programmes across Financial Services. The focus is designing scalable AI architectures that move beyond proof of concept into secure, production grade deployment across banking environments. Hiring across multiple levels, from Solution Architects through to senior technical leadership. What you'll be doing Designing AI and GenAI architecture strategies and roadmaps Building scalable AI/ML and Agentic AI platforms Working across LLMs, RAG, embeddings and semantic search Supporting AI deployment, governance and integration patterns Collaborating with engineering, data, DevOps and business teams Advising clients on AI platform capability and implementation strategy Environment Python LLMs, prompt engineering, fine tuning, RAG LangChain, LangGraph, Agent frameworks Vector databases and semantic search MLOps and LLMOps AWS, Azure, GCP, Databricks Containerisation, Kubernetes and GPU infrastructure Requirements Experience designing enterprise AI or ML architectures Strong understanding of cloud and modern data platforms Exposure to scalable AI deployment and integration patterns Financial Services or regulated industry experience essential Strong stakeholder engagement and communication skills Open to candidates from Manager through to Associate Director level. Seniority Level: Mid Senior level

Here at Humanoid, we believe in a future where robots amplify human potential. That's why we've set out on a mission to build the world's most capable, commercially-scalable, and safe humanoid robots. We're bringing that mission to life with HMND 01 Alpha - our rapidly developed humanoid platform now running in real industrial pilots - and we're growing the team to take it even further. About The Role We're hiring a Senior Dev/MLOps Engineer to join our Data & Compute Platform team based in London. What You'll Do Own and manage the full lifecycle of both ML models and core infrastructure - from development and deployment to monitoring and continuous improvement. Build and maintain robust CI/CD pipelines for both software and ML workflows. Ensure reliability, scalability, observability, and security of production systems and ML infrastructure. Automate deployment, orchestration, and environment management using modern DevOps tooling. Collaborate closely with software engineers, data scientists, and product teams to bring ML-powered features to production. Proactively detect, troubleshoot, and resolve infrastructure and model performance issues. Stay up to date with industry best practices in DevOps, MLOps, and infrastructure engineering. Document infrastructure, workflows, and operational procedures clearly and thoroughly. What We're Looking For Proven experience in a senior-level DevOps, MLOps, or related infrastructure-focused engineering role. Strong proficiency in Python and familiarity with ML frameworks such as TensorFlow or PyTorch. Deep experience with cloud platforms (AWS, GCP, or Azure) and container orchestration tools (Docker, Kubernetes). Solid understanding of CI/CD systems (e.g., GitHub Actions, GitLab CI, ArgoCD) and infrastructure-as-code tools (e.g., Terraform, Helm). Familiarity with data engineering concepts such as ETL pipelines, data lakes, and large-scale batch/stream processing. Ability to design scalable, secure, and observable systems in fast-moving environments. Strong debugging and problem-solving skills across distributed systems. Excellent collaboration and communication skills, with experience working in cross-functional teams. Understanding of security and compliance best practices for both software and ML systems. What We Offer Meaningful time off to rest and recharge: 23 days of annual leave (accrued), 15 days of paid sick leave, and paid company holidays. Fully funded private healthcare for UK employees, with broad provider access, virtual and in person care, and strong mental health and serious illness support. Equity included-we believe builders should share in what they build. Pension scheme with a total 8% contribution (5% employee, 3% employer) on full earnings. Free daily breakfast, catered lunch, and snacks in office. Collaboration with top tier engineers, researchers, and product experts in AI and robotics. Freedom to influence the product and own key initiatives.

Who We Are Allwyn Lottery Solutions is a global leader in digital lottery and gaming solutions and a proud subsidiary of Allwyn Entertainment Group, a multinational lottery operator with a strong presence in Austria, the Czech Republic, Greece, Cyprus, and Italy. Our mission is to make play better for all by developing cutting edge technology that enhances player experiences, drives engagement, and maximizes returns for good causes. What We Do We design and deliver innovative, scalable, and secure lottery solutions that evolve with the needs of players and operators. Our flagship platform, Genesis, provides a powerful foundation for lotteries worldwide, featuring: Player Account Management (PAM) for secure and seamless player experiences Draw-Based Games (DBG) for classic lottery draws Nexus Aggregator & Apollo RGS for e-Instants and Fast Play games Web & mobile applications for an enhanced and modern user experience Command Admin Portal for streamlined operations Optex Promotions to reward and engage players With a focus on cloud-based technologies, AI-driven analytics, and responsible gaming, we empower lotteries to reach new players, expand engagement, and achieve sustainable growth in an evolving digital landscape. At Allwyn Lottery Solutions, you'll be part of a forward thinking, collaborative, and innovative team that is shaping the future of iLottery. Overview The Business Intelligence & Data team builds the platforms and products that turn data into valuable business insights, powering everything from analytics and AI solutions to customer facing applications. As a Cloud Platform Engineer, you'll play a key role in designing, building, and operating a modern AWS cloud platform that supports large scale data processing, machine learning, APIs, and web applications. Working in a highly collaborative environment alongside Data Engineers, Developers, Data Scientists, and Architects, you'll help deliver secure, scalable, and automated cloud solutions while driving the evolution of a cloud native platform focused on reliability, performance, and innovation. This role combines AWS platform engineering, cloud networking, security, automation, serverless architecture, observability, and application platform operations. You will help shape the evolution of our cloud native platform while ensuring strong operational excellence, security, performance, and governance across both data services and data driven products. Key Accountabilities and Duties Design, build, and operate the cloud infrastructure and platform services that support data platforms, analytics workloads, AI/ML services, APIs, and web applications. Develop and maintain reusable infrastructure patterns, deployment frameworks, and automation capabilities using Infrastructure as Code. Build and optimise cloud native, serverless, and event driven architectures supporting both data processing workloads and user facing applications. Design and maintain secure and resilient cloud networking patterns, ensuring reliable connectivity between applications, data services, external integrations, and platform components. Implement and continuously improve security controls across identity and access management, encryption, secrets management, perimeter protection, vulnerability management, and threat detection. Design and maintain CI/CD and GitOps workflows for infrastructure, backend services, web applications, and platform components. Partner with Product Engineers to provide robust hosting, deployment, observability, scaling, and operational capabilities for internally developed applications and customer facing products. Implement and maintain monitoring, logging, alerting, and operational tooling to ensure platform health, application performance, and service availability. Support the deployment and operation of machine learning and AI powered services as part of the wider data platform ecosystem. Investigate and resolve complex infrastructure, networking, security, and application platform issues, performing root cause analysis and driving preventative improvements. Identify opportunities to improve automation, reliability, security, performance, scalability, and cost efficiency across the platform. Minimum Qualifications Degree in Computer Science, Information Technology, Engineering, or equivalent practical experience. 5+ years of experience in Platform Engineering, Cloud Engineering, DevOps, Site Reliability Engineering, Data Platform Engineering, or similar roles. Excellent verbal and written communication skills. Excellent command of the English language. Required Technical Skills Strong hands on experience designing, building, and operating production workloads on AWS, including serverless, event driven, and containerized architectures. Solid understanding of AWS cloud infrastructure, networking, and security, including routing, DNS, load balancing, TLS, network segmentation, VPN connectivity, IAM, encryption, secrets management, vulnerability management, perimeter protection, and security monitoring. Experience supporting data engineering, analytics, business intelligence, and reporting platforms within AWS environments. Proficiency with Infrastructure as Code (Terraform, OpenTofu, Ansible, or similar), automation using Python and/or Node.js, and building cloud native services. Experience implementing CI/CD pipelines, GitOps workflows, and modern cloud deployment practices, with a strong focus on automation and operational efficiency. Strong knowledge of observability, monitoring, alerting, incident response, and troubleshooting complex infrastructure, networking, security, and deployment issues. Desired Technical Skills Experience supporting machine learning workloads or MLOps practices in cloud environments. Experience with modern data lake, streaming, analytics, or cloud native BI architectures. Understanding of AWS cost optimisation and FinOps principles. Experience operating in regulated, security sensitive, or high availability environments. Experience with test automation frameworks such as PyTest, UnitTest, Vitest, Jest, or similar. AWS certifications in Architecture, DevOps, Security, Networking, Data, or Machine Learning. Required Competencies Strong analytical and problem solving skills, with the ability to diagnose complex technical issues, take ownership, and drive solutions through to completion. Self motivated and proactive, comfortable working in a lean, fast paced environment, contributing across multiple disciplines with minimal supervision. Systems thinking mindset with the ability to design, optimize, and make sound technical decisions for end to end platform architectures in ambiguous situations. Strong security awareness and understanding of operational risk, compliance, governance, and engineering best practices. Excellent collaboration, communication, and documentation skills, with the ability to work effectively across cross functional technical and business teams. Passion for automation, continuous improvement, engineering excellence, and staying current with emerging cloud, platform engineering, data, and AI technologies. At Allwyn LS, we know that great delivery starts with great people. Here's what we offer to support you and help you thrive: A dynamic team of experts who'll support your growth and share your ambition. A diverse, international environment full of opportunity and challenge. A comprehensive onboarding experience to set you up for success. Competitive salary with a performance based bonus. Health and life insurance for you and your family. Well being allowance. Extensive leave policy to support work life balance. Unlimited training resources and tools to support your development. 360 feedback framework to help you grow your impact. Employee Assistance Programme with professional counselling support. Flexible working options. A modern tech setup including Apple equipment and best in class tools. A stable, enjoyable working environment where delivery is valued. We're proud to be an Equal Opportunity Employer. Allwyn values diversity and inclusion and welcomes applications from all backgrounds. We make employment decisions based on business needs, role requirements, and individual qualifications - never on age, disability, gender identity, sexual orientation, pregnancy, race, religion, or background.

Who We Are Allwyn Lottery Solutions is a global leader in digital lottery and gaming solutions and a proud subsidiary of Allwyn Entertainment Group, a multinational lottery operator with a strong presence in Austria, the Czech Republic, Greece, Cyprus, and Italy. Our mission is to make play better for all by developing cutting edge technology that enhances player experiences, drives engagement, and maximizes returns for good causes. What We Do We design and deliver innovative, scalable, and secure lottery solutions that evolve with the needs of players and operators. Our flagship platform, Genesis, provides a powerful foundation for lotteries worldwide, featuring: Player Account Management (PAM) for secure and seamless player experiences Draw-Based Games (DBG) for classic lottery draws Nexus Aggregator & Apollo RGS for e-Instants and Fast Play games Web & mobile applications for an enhanced and modern user experience Command Admin Portal for streamlined operations Optex Promotions to reward and engage players With a focus on cloud-based technologies, AI-driven analytics, and responsible gaming, we empower lotteries to reach new players, expand engagement, and achieve sustainable growth in an evolving digital landscape. At Allwyn Lottery Solutions, you'll be part of a forward thinking, collaborative, and innovative team that is shaping the future of iLottery. Overview The Business Intelligence & Data team builds the platforms and products that turn data into valuable business insights, powering everything from analytics and AI solutions to customer facing applications. As a Cloud Platform Engineer, you'll play a key role in designing, building, and operating a modern AWS cloud platform that supports large scale data processing, machine learning, APIs, and web applications. Working in a highly collaborative environment alongside Data Engineers, Developers, Data Scientists, and Architects, you'll help deliver secure, scalable, and automated cloud solutions while driving the evolution of a cloud native platform focused on reliability, performance, and innovation. This role combines AWS platform engineering, cloud networking, security, automation, serverless architecture, observability, and application platform operations. You will help shape the evolution of our cloud native platform while ensuring strong operational excellence, security, performance, and governance across both data services and data driven products. Key Accountabilities and Duties Design, build, and operate the cloud infrastructure and platform services that support data platforms, analytics workloads, AI/ML services, APIs, and web applications. Develop and maintain reusable infrastructure patterns, deployment frameworks, and automation capabilities using Infrastructure as Code. Build and optimise cloud native, serverless, and event driven architectures supporting both data processing workloads and user facing applications. Design and maintain secure and resilient cloud networking patterns, ensuring reliable connectivity between applications, data services, external integrations, and platform components. Implement and continuously improve security controls across identity and access management, encryption, secrets management, perimeter protection, vulnerability management, and threat detection. Design and maintain CI/CD and GitOps workflows for infrastructure, backend services, web applications, and platform components. Partner with Product Engineers to provide robust hosting, deployment, observability, scaling, and operational capabilities for internally developed applications and customer facing products. Implement and maintain monitoring, logging, alerting, and operational tooling to ensure platform health, application performance, and service availability. Support the deployment and operation of machine learning and AI powered services as part of the wider data platform ecosystem. Investigate and resolve complex infrastructure, networking, security, and application platform issues, performing root cause analysis and driving preventative improvements. Identify opportunities to improve automation, reliability, security, performance, scalability, and cost efficiency across the platform. Minimum Qualifications Degree in Computer Science, Information Technology, Engineering, or equivalent practical experience. 5+ years of experience in Platform Engineering, Cloud Engineering, DevOps, Site Reliability Engineering, Data Platform Engineering, or similar roles. Excellent verbal and written communication skills. Excellent command of the English language. Required Technical Skills Strong hands on experience designing, building, and operating production workloads on AWS, including serverless, event driven, and containerized architectures. Solid understanding of AWS cloud infrastructure, networking, and security, including routing, DNS, load balancing, TLS, network segmentation, VPN connectivity, IAM, encryption, secrets management, vulnerability management, perimeter protection, and security monitoring. Experience supporting data engineering, analytics, business intelligence, and reporting platforms within AWS environments. Proficiency with Infrastructure as Code (Terraform, OpenTofu, Ansible, or similar), automation using Python and/or Node.js, and building cloud native services. Experience implementing CI/CD pipelines, GitOps workflows, and modern cloud deployment practices, with a strong focus on automation and operational efficiency. Strong knowledge of observability, monitoring, alerting, incident response, and troubleshooting complex infrastructure, networking, security, and deployment issues. Desired Technical Skills Experience supporting machine learning workloads or MLOps practices in cloud environments. Experience with modern data lake, streaming, analytics, or cloud native BI architectures. Understanding of AWS cost optimisation and FinOps principles. Experience operating in regulated, security sensitive, or high availability environments. Experience with test automation frameworks such as PyTest, UnitTest, Vitest, Jest, or similar. AWS certifications in Architecture, DevOps, Security, Networking, Data, or Machine Learning. Required Competencies Strong analytical and problem solving skills, with the ability to diagnose complex technical issues, take ownership, and drive solutions through to completion. Self motivated and proactive, comfortable working in a lean, fast paced environment, contributing across multiple disciplines with minimal supervision. Systems thinking mindset with the ability to design, optimize, and make sound technical decisions for end to end platform architectures in ambiguous situations. Strong security awareness and understanding of operational risk, compliance, governance, and engineering best practices. Excellent collaboration, communication, and documentation skills, with the ability to work effectively across cross functional technical and business teams. Passion for automation, continuous improvement, engineering excellence, and staying current with emerging cloud, platform engineering, data, and AI technologies. At Allwyn LS, we know that great delivery starts with great people. Here's what we offer to support you and help you thrive: A dynamic team of experts who'll support your growth and share your ambition. A diverse, international environment full of opportunity and challenge. A comprehensive onboarding experience to set you up for success. Competitive salary with a performance based bonus. Health and life insurance for you and your family. Well being allowance. Extensive leave policy to support work life balance. Unlimited training resources and tools to support your development. 360 feedback framework to help you grow your impact. Employee Assistance Programme with professional counselling support. Flexible working options. A modern tech setup including Apple equipment and best in class tools. A stable, enjoyable working environment where delivery is valued. We're proud to be an Equal Opportunity Employer. Allwyn values diversity and inclusion and welcomes applications from all backgrounds. We make employment decisions based on business needs, role requirements, and individual qualifications - never on age, disability, gender identity, sexual orientation, pregnancy, race, religion, or background.

Senior DeveloperApplylocations: Kings Cross, Londontime type: Full timeposted on: Posted 5 Days Agojob requisition id: UMG-25161Music is Universal It's the passionate and dedicated team at Universal Music who help make us the world's leading music company. From A&R to finance, legal to digital, sales to marketing, Universal Music is the place to grow and develop your career within a truly commercial and innovative business that leads in everything it does.Everyone is welcome to apply for our roles, and we are determined to ensure that no applicant or employee receives less favourable treatment because of gender, race, disability, sexual orientation, religion, belief, age, marital status, background, pregnancy, or caring responsibilities. We also recognise the importance of diversity of thought within our teams and are fully committed to embracing the talents of people with autism, dyslexia, ADHD, and other forms of neurocognitive variation.We will always seek to make appropriate adjustments to recruitment, workplaces, and work processes to be fully inclusive to people with different needs and working styles. If you need us to make any reasonable adjustments for you from application onwards, including alternatives to the online form or to disclose a neurocognitive condition, please email . Department With a global footprint, the Universal Music Group Royalty and Copyright Product Team designs, develops, delivers and maintains a number of technical solutions to calculate royalty accountings in a timely and accurate manner to our valued artists. We're also providing them with an extent and detailed visibility of these earning from various sources of digital incomes.The team continuously collaborates with our international business teams to deliver innovative solutions as well as supporting best practices and new processes for a better royalty flow. The Role The Senior Developer will be responsible for designing, developing and maintaining backend services using .NET Core / ASP.NET Core on AWS, with a strong focus on serverless architectures and event-driven systems using Kafka / AWS MSK. The Senior Developer will also work with containerised workloads on Kubernetes, and have exposure to modern DevOps and CI/CD practices.The Senior Developer will be part of an agile product team, collaborating closely with product owners, business analysts, engineers, architects, QAs and DevOps to deliver secure, performant and reliable solutions. Key Responsibilities Be Technical Design, build and maintain backend services and APIs using .NET Core / ASP.NET Core. Develop modern web UIs (React / Angular / TypeScript or similar) and integrate them with backend services. Develop and support AWS serverless solutions (e.g. Lambda, API Gateway, Step Functions, DynamoDB, S3). Implement event-driven architectures using Kafka (preferably on AWS MSK) for high-throughput, near real-time processing. Work with Docker and Kubernetes to build, deploy and run containerised services. Contribute to the design and implementation of scalable, secure and resilient cloud architectures. Work with DevOps engineers to enhance CI/CD pipelines, automated testing and deployment processes. Model and optimise data across SQL and NoSQL stores. Be Collaborative Drive code quality: write clean, efficient, well-documented and reusable code. Participate in code reviews, technical discussions and agile ceremonies. Troubleshoot production issues and improve monitoring, logging and alerting across services. Collaborate with stakeholders to refine requirements and deliver high-quality solutions on time. Build positive relationships with rest of development teams. Strong communication, and interpersonal skills. Skills and Experience required Must have Strong commercial experience with .NET Core / ASP.NET Core for backend development. Proven experience building solutions on AWS, ideally including serverless services (Lambda, API Gateway, DynamoDB, etc.). Hands-on experience with Kafka (preferably AWS MSK) for messaging/stream processing. Experience with Docker and Kubernetes for container orchestration. Good understanding of DevOps concepts, with practical experience using Git and working with CI/CD tooling (e.g. GitHub Actions, Azure DevOps, GitLab CI or similar). Experience with both SQL (e.g. SQL Server, PostgreSQL, MySQL) and NoSQL databases (e.g. DynamoDB, MongoDB). Exposure to Big Data tools/platforms and data pipelines (streaming and/or batch) is strongly preferred. Comfortable working in an agile environment (Scrum/Kanban). Strong problem-solving skills, attention to detail and a collaborative mindset. Ability to take ownership, solve complex problems and mentor more junior engineers where required. Nice to have Experience delivering systems on GCP. Knowledge of microservices and event-driven architectures. Experience with Infrastructure as Code (e.g. CloudFormation, CDK, Terraform). Any experience with MCP (Model Context Protocol) and/or MLOps (e.g. model deployment pipelines, monitoring and lifecycle management) is highly desirable. Understanding of compliance requirement around SDLC, ITGC,ITAC. Key Behavioural/Personality Traits The Senior Developer will demonstrate strong collaboration skillset with the rest of the development team, as well as producing high-quality code and showing initiative by identifying solutions to increase productivity. About UMG UK We are Universal Music Group UK - the UK's leading music-based entertainment company. We exist to shape culture through the power of artistry. We help UK artists produce, distribute and promote the most critically acclaimed and commercially successful music to inspire and entertain fans at home and around the world. Bonus Tracks: Your Benefits Group Personal Pension Scheme (between 3% and 9%) Private Medical Insurance 25 paid days of annual leave Interest Free Season Ticket Loan Holiday Purchase scheme Dental and Travel Insurance options Cycle to Work Scheme Salary Sacrifice Cars Subsidised Gym Membership Employee Discounts (Reward Gateway)Just So You Know The company presents this job description as a guide to the major areas and duties for which the jobholder is accountable. However, the business operates in an environment that demands change and the jobholder's specific responsibilities and activities will vary and develop. Therefore, the job description should be seen as indicative and not as a permanent, definitive, and exhaustive statement.

Your profile Are you a senior DevOps and infrastructure engineer who enjoys building reliable cloud platforms, enabling engineering teams, and using AI to remove operational complexity? At Cenosco, we buildAsset Integrity Management software trusted by global leaders in Oil & Gas, Chemicals, and Energy. We are looking for someone who can strengthen our DevOps foundation, evolve our infrastructure, and help us use AI-powered tools to automate how we build, deploy, monitor, and operate our platform. This role is primarily focused onDevOps, infrastructure enablement, IaC, deployment automation, and platform reliability. You will also play an important part in shaping how we use AI and agentic tooling (i.e. Copilot, Cursor, Codex, and similar tools) to make DevOps work faster, smarter, and more scalable. What You'll Do DevOps, Infrastructure & Platform Enablement Design, build, andmaintainscalable cloud infrastructure on Azure, with a strong focus on reliability, security, performance, and operational simplicity. Own and improveInfrastructure as Code practices usingTerraform, Pulumi, or similar tools, creating reusable patterns that help teams provision and manage environments consistently. Build,optimize, and automate CI/CD pipelines for application, infrastructure, and platform deployments across environments. Enable engineering teams by creating self-service infrastructure, deployment templates, automation scripts, documentation, and platform standards. Drive containerization and orchestration practices usingKubernetesand Talos, ensuring our platform can scale reliably and efficiently. Embed security, compliance, monitoring, and disaster recovery considerations into infrastructure and deployment workflows from the start. AI-Assisted DevOps Automation Use AI-assisted and agentic tools to automate repetitive DevOps work, including pipeline creation,IaCgeneration, environment provisioning, deployment workflows, and operational runbooks. Experiment with tools such asGitHub Copilot,Cursor,Codex, and similar solutions to improve engineering productivity and reduce manual infrastructure effort. Identifyopportunities to apply AI to troubleshooting, incident response, monitoring, release management, and platform operations. Help define practical, secure, and scalable ways of using AI in DevOps processes, whilemaintainingstrong engineering standards and governance. Observability, Reliability & Continuous Improvement Improve monitoring, alerting, logging, and observability practices to help teams detect issues earlier and resolve incidents faster. Analyze platform performance, deployment quality, incidents, and recurring operational patterns to recommend practical improvements. Collaborate closely with software engineering, security, product, and architecture teams to continuously improve our delivery andinfrastructure standards. What You'll Need 8+ years of professional experience in DevOps&Infrastructure engineering,Platform engineering, or a similar role in a SaaS or product-based environment. Hands-on experience with Azure(or similar)cloud services and cloud-native infrastructure design Strong practical knowledge of CI/CD, deployment automation, release pipelines, and environment management. Experience with Infrastructure as Code tools such as Terraform,Pulumi,or similar technologies. Good understanding ofcontainers,Kubernetes, AKS,Ansilbe, Packer, networking, security, monitoring, and reliability practices. Practical experience using AI-assisted coding or automation tools, or a strong interest in applying them to DevOps and infrastructure workflows. A strong enablement mindset: you enjoy creating standards, reusable solutions, documentation, and automation that help engineering teams move faster andmore safely. Bonus Points Experience using machine learning, heuristic analysis, or AI-assisted techniques to analyze logs, detect anomalies, spot trends, and support proactive troubleshooting. Experience building internal developer platforms, self-service deployment workflows, golden paths, or platform engineering tooling. Experience with security automation, policy-as-code, cost optimization, or FinOps practices in cloud environments. Exposure to AI infrastructure,MLOps, data pipelines, or supporting engineering teams that build AI-enabled products. Working Locations Croatia, Zagreb - Hybrid Croatia, Pula - Hybrid UK - Remote Why Join Us? Join a product-focused engineering environment where DevOps and infrastructure directly enable scale, reliability, and innovation. Shape modern cloud, infrastructure, and deployment practices across a growing SaaS platform. Introduce practical AI-driven automation that helps engineering teams work faster, smarter, and with greater confidence. Work on meaningful platform improvements that reduce manual effort, improve reliability, and create a better developer experience.

Overview Position Overview: As a Forward Deployed AI Engineer within Convatec's AI Centre of Excellence, you will help turn AI opportunities into practical, production-ready solutions that improve how our business works. Embedded directly with business teams, you will take ownership of AI-enabled workflows from discovery and design through to build, testing, deployment, monitoring and handover. This is a senior, hands-on delivery role for someone who can work independently across architecture, integration, DevOps, MLOps, AIOps, data engineering and governance. You will make technical decisions, solve complex integration challenges and ensure AI solutions are reliable, scalable and safe to run in live business environments. You will work with technologies such as Microsoft Copilot Studio, Microsoft Fabric, Azure DevOps, Azure AI Foundry and SAP Joule, helping to design, build and deploy AI workflows that connect into real operational processes across Convatec. We are looking for someone who is comfortable being the senior technical voice on an initiative: setting standards, guiding others, managing technical risks and ensuring solutions are successfully handed over to the teams who will use and support them. Responsibilities Workflow implementation and engineering: Design, build and deploy AI-enabled workflows using Azure AI Foundry, Microsoft Copilot Studio, Microsoft Fabric and SAP Joule. This includes agent orchestration, automation triggers, prompt integration, exception handling and reusable delivery patterns. API integration and service connectivity: Connect AI workflows to enterprise systems through REST APIs, event streams and Microsoft Fabric data pipelines, ensuring secure and reliable data flows across platforms such as SAP, Salesforce and Convatec's data lake. Technical leadership and standards: Act as the senior technical voice within embedded initiatives, setting engineering standards, guiding Applied AI Engineers and business teams, and making sound architecture and integration decisions within agreed guardrails. Testing, validation and quality assurance: Plan and execute functional, regression and edge-case testing, including failure scenarios, fallback paths, escalation triggers and data quality checks. Assess when workflows are ready for production release. Rapid prototyping and feasibility assessment: Build timeboxed prototypes in the AI Landing Zone sandbox to test technical options, demonstrate value and provide clear go/no-go recommendations before full delivery. DevOps, MLOps and AIOps ownership: Implement and maintain CI/CD, monitor and release pipelines using Azure DevOps, including version control, rollback capability, automated testing and production health monitoring. Documentation and operational handover: Produce clear technical documentation and handover materials so business and operational teams can maintain, monitor and extend AI workflows after delivery. Decision-making authority: Make technical recommendations on workflow architecture, integration patterns, tooling choices, production readiness and handover quality within the scope of each initiative. Skills & Experience Essential: Minimum 4+ years' experience in software engineering, AI/ML workflow delivery or systems integration, with a demonstrable track record of full-stack delivery in production AI environments. Minimum 2+ years' operating in a senior or lead technical capacity, making independent architectural decisions and guiding other engineers without formal line management authority. Hands-on, production-grade experience across DevOps, MLOps and AIOps - CI/CD pipeline ownership, model versioning, automated testing and live system monitoring - not as adjacent knowledge but as daily practice. Strong proficiency in Python and SQL; solid REST and event-driven API integration experience including enterprise systems such as SAP (via SAP Joule) or Salesforce. Hands-on experience with Azure AI Foundry, Microsoft Copilot Studio and Microsoft Fabric in production delivery contexts. Demonstrated ability to self-direct across the full delivery lifecycle - from discovery and design through to production deployment and business handover - without close technical supervision. Experience working directly with business stakeholders: translating operational requirements into engineering decisions, managing expectations and owning adoption outcomes. Desirable Experience with SAP Joule or integrating agentic AI solutions with SAP business processes. Familiarity with AI Landing Zone design patterns, guardrails and governance frameworks. Experience with containerization (Docker/Kubernetes) and cloud-native deployment patterns on Azure. Understanding of multi-agent coordination patterns using Copilot Studio or Azure AI Foundry. Knowledge of healthcare data privacy requirements including GDPR or HIPAA. Soft Skills Self-directed and comfortable working through ambiguity. Technically credible, with the confidence to set standards and challenge approaches where needed. Outcome-focused, with strong ownership of delivery quality and production reliability. Adaptable, able to work across multiple business areas and changing priorities. Clear communicator, able to explain technical decisions in a way that business stakeholders can understand and act on. Education/Qualifications Bachelor's or Master's degree in Computer Science, Software Engineering, Information Systems or a related field, or equivalent practical experience demonstrated through a strong delivery track record. Relevant Azure certifications (e.g. Azure Developer Associate, Azure Data Engineer Associate, Azure DevOps Engineer Expert) or MLOps/AIOps are desirable. Travel & Working Conditions Travel up to 10% of the time, mostly within Europe. Hybrid working model - 1 day per week on-site at our London office. Legal and Compliance Equal opportunities Convatec provides equal employment opportunities for all current employees and applicants for employment. This policy means that no one will be discriminated against because of race, religion, creed, color, national origin, nationality, citizenship, ancestry, sex, age, marital status, physical or mental disability, affectional or sexual orientation, gender identity, military or veteran status, genetic predisposing characteristics or any other basis prohibited by law. Notice to Agency and Search Firm Representatives Convatec is not accepting unsolicited resumes from agencies and/or search firms for this job posting. Resumes submitted to any Convatec employee by a third party agency and/or search firm without a valid written and signed search agreement will become the sole property of Convatec. No fee will be paid if a candidate is hired for this position as a result of an unsolicited agency or search firm referral. Contact:

At TEKEVER, we lead innovation in Europe as the European leader in unmanned technology, where cutting edge advancements meet unparalleled innovation. Digital Defence Security Space We operate across four strategic areas, combining artificial intelligence, systems engineering, data science, and aerospace technology to tackle global challenges - from protecting people and critical infrastructure to exploring space. We offer a unique surveillance as a service solution that delivers real time intelligence, enhancing maritime safety and saving lives. Our products and services support strategic and operational decisions in the most demanding environments - whether at sea, on land, in space, or in cyberspace. Become part of a dynamic, multidisciplinary, and mission driven team that is transforming maritime surveillance and redefining global safety standards. At TEKEVER, our mission is to provide limitless support through mission oriented game changers, delivering the right information at the right time to empower critical decision making. If you're passionate about technology and eager to shape the future - TEKEVER is the place for you. Mission As a Data & ML Platform Engineer, you will play a critical role in designing, building and maintaining the infrastructure that powers our data processing pipelines and machine learning workflows that support our data driven initiatives, as well as supporting the evolution of our Data & AI Platform. You will work at the intersection of data engineering, MLOps, and platform development and ensure that our data & AI infrastructure is robust, scalable and efficient. The ideal candidate will have a strong background in platform engineering, with experience in data science, machine learning and or data engineering. Responsibilities Design and implement scalable data and ML infrastructure using modern cloud and on prem distributed technologies and frameworks. Design, develop and maintain scalable and efficient data pipelines to collect, process and store large volumes of data from various sources. Manage and optimise databases and data warehouses to ensure data integrity, performance and availability. Integrate data from multiple sources, including APIs, databases and external data providers, to create unified datasets for analysis. Develop self service tools that enable stakeholders to extract insights from Data and Machine Learning models. Support the expansion of our Data & AI Platform. Ensure data security, privacy and compliance. Implement data validation and quality assurance processes to ensure the accuracy and consistency of data. Work closely with data scientists, analysts and other stakeholders to understand platform requirements and provide the necessary data infrastructure and support. Implement monitoring, observability and alerting for data and ML systems and optimise for performance, reliability and cost effectiveness. Maintain comprehensive documentation of platform components, APIs and workflows to ensure knowledge sharing and user adoption (e.g. data pipelines, database schemas, Machine Learning systems). Profile and requirements Education: Bachelor's or Master's degree in Computer Science, Engineering, Information Systems, or a related field. Preferred location: UK, Portugal, France and/or Spain. Experience: 3+ years of experience in data & ML platform engineering or a similar role. Analytical Skills: Strong analytical and problem solving skills with a focus on delivering scalable and efficient data solutions. Communication: Excellent verbal and written communication skills, with the ability to effectively collaborate with technical and non technical stakeholders. Language Requirements: Advanced proficiency in Portuguese and English, with proven fluency at the C2 level in both languages. Attention to Detail: High attention to detail and a commitment to ensuring data quality and accuracy. Adaptability: Ability to work in a fast paced, dynamic environment and manage multiple priorities simultaneously. Technical Skills Proficiency in programming languages such as Python, Go, Java, or Rust. Strong knowledge of containerisation technologies (e.g. Docker) and orchestration systems (e.g. Kubernetes) in production environments. Experience with SQL, database management systems (e.g., MySQL, PostgreSQL, SQL Server), data modelling and schema design. Experience with cloud platforms (e.g., AWS, Azure, Google Cloud) and their data services, with a focus on Google Cloud. Familiarity with big data technologies (e.g. Spark), data warehousing solutions, data pipeline orchestration (e.g. Airflow), and database systems (SQL and NoSQL). Design and manage MLOps pipelines to support model training, deployment and monitoring at scale. Experience implementing observability stacks and logging pipelines (e.g., Prometheus, Grafana, Loki, ELK). Experience with IaC frameworks (e.g. Ansible, Terraform). Understanding of DevOps best practices and tools: GIT, CI/CD, telemetry and monitoring, etc. What we have to offer you At TEKEVER, we offer a comprehensive package designed to reward, support and develop our people. This includes a highly competitive salary with discretionary annual bonus and a company pension contribution match of up to 10%. To support your well being, we provide 25 days annual leave plus Bank Holidays, Private Medical Insurance (with optional family cover), Private Dental care and an Employee Assistance Programme. We are deeply committed to investing in future talent; our scale allows us to provide clear career development opportunities and dedicated initiatives to boost your skill sets, ensuring you remain future ready for the evolving workplace. Furthermore, our team enjoys a flexible hybrid working model, typically three days a week at our core UK sites like Bristol, and access to a bespoke rewards platform featuring a variety of high street discounts and salary sacrifice schemes, including Electric Car, Cycle to Work and Technology options.

Music is UniversalIt's the passionate and dedicated team at Universal Music who help make us the world's leading music company. From A&R to finance, legal to digital, sales to marketing, Universal Music is the place to grow and develop your career within a truly commercial and innovative business that leads in everything it does.Everyone is welcome to apply for our roles, and we are determined to ensure that no applicant or employee receives less favourable treatment because of gender, race, disability, sexual orientation, religion, belief, age, marital status, background, pregnancy, or caring responsibilities. We also recognise the importance of diversity of thought within our teams and are fully committed to embracing the talents of people with autism, dyslexia, ADHD, and other forms of neurocognitive variation.We will always seek to make appropriate adjustments to recruitment, workplaces, and work processes to be fully inclusive to people with different needs and working styles. If you need us to make any reasonable adjustments for you from application onwards, including alternatives to the online form or to disclose a neurocognitive condition, please email a global footprint, the Universal Music Group Royalty and Copyright Product Team designs, develops, delivers and maintains a number of technical solutions to calculate royalty accountings in a timely and accurate manner to our valued artists. We're also providing them with an extent and detailed visibility of these earning from various sources of digital incomes.The team continuously collaborates with our international business teams to deliver innovative solutions as well as supporting best practices and new processes for a better royalty flow.The RoleThe Senior Developer will be responsible for designing, developing and maintaining backend services using .NET Core / ASP.NET Core on AWS, with a strong focus on serverless architectures and event-driven systems using Kafka / AWS MSK. The Senior Developer will also work with containerised workloads on Kubernetes, and have exposure to modern DevOps and CI/CD practices.The Senior Developer will be part of an agile product team, collaborating closely with product owners, business analysts, engineers, architects, QAs and DevOps to deliver secure, performant and reliable solutions.Key ResponsibilitiesBe TechnicalDesign, build and maintain backend services and APIs using .NET Core / ASP.NET Core.Develop modern web UIs (React / Angular / TypeScript or similar) and integrate them with backend services.Develop and support AWS serverless solutions (e.g. Lambda, API Gateway, Step Functions, DynamoDB, S3).Implement event-driven architectures using Kafka (preferably on AWS MSK) for high-throughput, near real-time processing.Work with Docker and Kubernetes to build, deploy and run containerised services.Contribute to the design and implementation of scalable, secure and resilient cloud architectures.Work with DevOps engineers to enhance CI/CD pipelines, automated testing and deployment processes.Model and optimise data across SQL and NoSQL stores.Be CollaborativeDrive code quality: write clean, efficient, well-documented and reusable code.Participate in code reviews, technical discussions and agile ceremonies.Troubleshoot production issues and improve monitoring, logging and alerting across services.Collaborate with stakeholders to refine requirements and deliver high-quality solutions on time.Build positive relationships with rest of development teams.Strong communication, and interpersonal skills.Skills and Experience requiredMust haveStrong commercial experience with .NET Core / ASP.NET Core for backend development.Proven experience building solutions on AWS, ideally including serverless services (Lambda, API Gateway, DynamoDB, etc.).Hands-on experience with Kafka (preferably AWS MSK) for messaging/stream processing.Experience with Docker and Kubernetes for container orchestration.Good understanding of DevOps concepts, with practical experience using Git and working with CI/CD tooling (e.g. GitHub Actions, Azure DevOps, GitLab CI or similar).Experience with both SQL (e.g. SQL Server, PostgreSQL, MySQL) and NoSQL databases (e.g. DynamoDB, MongoDB).Exposure to Big Data tools/platforms and data pipelines (streaming and/or batch) is strongly preferred.Comfortable working in an agile environment (Scrum/Kanban).Strong problem-solving skills, attention to detail and a collaborative mindset.Ability to take ownership, solve complex problems and mentor more junior engineers where required.Nice to haveExperience delivering systems on GCP.Knowledge of microservices and event-driven architectures.Experience with Infrastructure as Code (e.g. CloudFormation, CDK, Terraform).Any experience with MCP (Model Context Protocol) and/or MLOps (e.g. model deployment pipelines, monitoring and lifecycle management) is highly desirable.Understanding of compliance requirement around SDLC, ITGC,ITAC.Key Behavioural/Personality TraitsThe Senior Developer will demonstrate strong collaboration skillset with the rest of the development team, as well as producing high-quality code and showing initiative by identifying solutions to increase productivity.About UMG UKWe are Universal Music Group UK - the UK's leading music-based entertainment company. We exist to shape culture through the power of artistry. We help UK artists produce, distribute and promote the most critically acclaimed and commercially successful music to inspire and entertain fans at home and around the world.Bonus Tracks: Your BenefitsGroup Personal Pension Scheme (between 3% and 9%)Private Medical Insurance25 paid days of annual leaveInterest Free Season Ticket LoanHoliday Purchase schemeDental and Travel Insurance optionsCycle to Work SchemeSalary Sacrifice CarsSubsidised Gym MembershipEmployee Discounts (Reward Gateway)Just So You Know The company presents this job description as a guide to the major areas and duties for which the jobholder is accountable. However, the business operates in an environment that demands change and the jobholder's specific responsibilities and activities will vary and develop. Therefore, the job description should be seen as indicative and not as a permanent, definitive, and exhaustive statement.Job Category:Universal Music Group