Job Description:

Lead AI Engineer

Leeds or Edinburgh

£72,000 - £108,000

Your new role

The Data, Technology and Innovation (DTI) division enables the group 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 group), the department will partner with business leads to shape and deliver work in priority areas - Authorisations, SPC, EMO and Anti Money Laundering.

Responsibilities

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

Experience needed

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

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

Working knowledge of modern DevOps 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)

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

AI engineering experience delivering LLM-enabled systems using LLM APIs/Bedrock, including RAG architectures, vector databases and orchestration frameworks

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

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

Benefits

28 days annual leave plus bank holidays

Hybrid model where employees work a minimum of 40% in the office each month (expectation of 50% for senior leaders).

Non-contributory pension (8-12% depending on age) and life assurance at eight times your salary

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