Lead AI Engineer

• We regulate financial services firms in the UK, to keep financial markets fair, thriving and effective. By joining us, you’ll play a key part in protecting consumers, driving economic growth, and shaping the future of UK finance services
• The Data, Technology and Innovation (DTI) division enables the FCA to be a digital-first, data-led smart regulator by delivering a secure, agile, and cost-effective technology and data ecosystem that drives better decisions, transparency, and operational efficiency
• Working alongside the wider AI Programme (which will continue to oversee/coordinate AI activity across the FCA), the department will partner with business leads to shape and deliver work in priority areas — Authorisations, SPC, EMO and Anti‑Money Laundering
• Standardise and advance reusable AI solution patterns and reference architectures, improving cross-team consistency and delivery quality to enable more reliable and scalable product development
• Establish end-to-end technical architectures for LLM-enabled systems, covering data pipelines, retrieval/RAG, prompt orchestration and agent workflows to support robust and effective AI implementation
• Analyse complex constraints across product, data, security, legal and operations, translating them into clear standards and recommendations to enable delivery of highly complex AI solutions
• Enhance CI/CD pipelines for AI systems, introducing automation, traceability and controlled release processes to ensure safe and repeatable deployments
• Define monitoring, observability and operational strategies, improving visibility across quality, performance, safety, cost and reliability to support effective issue diagnosis and resolution
• Set standards for prompt engineering, evaluation and testing, enhancing solution quality and behavioural consistency to support teams in resolving complex model challenges
• Advance digital and data-driven methods by shaping organisational practices and innovation efforts that produce measurable improvements in performance and efficiency
• Collaborate with senior stakeholders to deliver analytics-led solutions, addressing regulatory challenges and generating organisational impact to contribute to improved decision-making and long-term economic outcomes

• Hybrid working (work from home up to 60% of your time)
• 25 days holiday per year plus bank holidays
• Private healthcare with Bupa
• Life assurance
• A non-contributory Pension of at least 8%
• Income protection

Experience delivering cloud solutions on AWS including deploying, operating and troubleshooting services in live environments

Extensive backend engineering experience building production services such as APIs and microservices with solid software engineering fundamentals combined with experience developing technical architecture and designs and taking them through enterprise review processes

Demonstrable capability in prompt design and in setting evaluation/testing approaches for LLM solutions (quality, safety/guardrails and performance), including defining measurable success criteria

DevOps skills including CI/CD pipelines, containerisation and monitoring/observability, with experience defining release and operating practices for AI services

Experience Leading Engineering teams: providing technical guidance, aligning on standards/patterns, and adapting plans to resolve delivery and operational challenges

Working knowledge of modern Dev Ops practices such as CI/CD, containerisation and monitoring with experience collaborating with engineers to deliver iteratively

Solid backend engineering experience, with experience designing, building and running reliable services in production (performance, resilience and security)
AI engineering experience delivering LLM-enabled systems using LLM APIs/Bedrock, including RAG architectures, vector databases and orchestration frameworks

Direct experience building and operating solutions on AWS, including AWS AI services and the supporting platform services required for production delivery