Lead AI Engineer

Overview

In this Lead AI Engineer role, you will shape scalable AI systems within the FCA’s Data, Technology and Innovation division. You’ll establish end-to-end architectures for LLM-enabled solutions and drive reliable, secure deployments in collaboration with senior stakeholders. You’ll raise the bar on standards for prompt design, testing, and observability while aligning AI work with regulatory priorities. This is a chance to impact how AI supports decisions that protect consumers and support economic growth.

Pay / Benefits

• 28 days annual leave plus bank holidays
• Hybrid model with in-office requirements
• Non-contributory pension (8–12%) and life assurance
• Private healthcare with Bupa, income protection, and EAP
• 35 hours of paid volunteering annually
• Flexible benefits scheme

Responsibilities

• Standardise reusable AI patterns and reference architectures to improve cross-team delivery quality
• Architect LLM-enabled systems with data pipelines, retrieval/RAG, and agent workflows
• Translate complex constraints into standards to enable delivery of AI solutions
• Enhance CI/CD pipelines for AI with automation and traceability
• Define monitoring, observability, and operational strategies for AI systems
• Set standards for prompt engineering, evaluation and testing
• Advance data-driven methods to improve performance and efficiency
• Collaborate with senior stakeholders to deliver analytics-led solutions addressing regulatory challenges

Key requirements

• Extensive backend engineering experience with production services (APIs/microservices)
• Experience delivering cloud solutions on AWS
• Knowledge of DevOps practices (CI/CD, containerisation, monitoring)
• Solid backend design/build/run of production services (performance, security)
• Experience building and operating AWS AI services and platform services for production
• AI engineering experience with LLM-enabled systems (RAG, vector databases, orchestration)
• DevOps skills with CI/CD, containers, monitoring/observability and release practices
• Experience leading engineering teams and providing technical guidance
• Demonstrable capability in prompt design and evaluation/testing for LLM solutions

• leadership of engineering teams
• stakeholder collaboration
• analytical problem-solving
• AWS cloud expertise
• LLM APIs/Bedrock
• RAG architectures

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