Lead AI Engineer

Reposted Yesterday
Be an Early Applicant
3 Locations
In-Office
72K-120K Annually
Senior level
Fintech • Software • Financial Services
The Role
Define and standardise end-to-end LLM architectures and reusable AI solution patterns. Design data pipelines, RAG, prompt orchestration and CI/CD for safe production deployment. Set monitoring, evaluation and prompt-testing standards. Lead engineering teams, address product/data/security/legal constraints, and collaborate with stakeholders to deliver AI solutions for regulatory priorities.
Summary Generated by Built In

Job Title: Lead AI Engineer 

Division: Data, Technology and Innovation 

Department: AI Product Delivery 

  • Salary: National (Edinburgh and Leeds) ranging from £72,100 to £108,000 and London from £79,300 to £120,000 per annum (salary offered will be based on skills and experience) 

  • This role is graded as: Technical Specialist – Regulatory  

  • Your external recruitment contact is Benjamin via [email protected].  

  • Your internal recruitment contact is Lauren via [email protected] 

  • Applications must be submitted through our online portal. Applications sent via social media or email will not be accepted. 

  

About the FCA and team  

  

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.  

  

Role 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 

Skills required  

Minimum: 

  • 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 

Essential: 

  • 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 

  • Colleagues spend a minimum of 50% of their working time in the office each month (60% for Directors and Executive Directors) across our London, Leeds and Edinburgh offices.

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

  • Private healthcare with Bupa, income protection, and 24/7 Employee Assistance 

  • 35 hours of paid volunteering annually 

  • A flexible benefits scheme designed around your lifestyle 

  

For a full list of our benefits, and our recruitment process as a whole visit our benefits page. 

  

Our values & culture  

  

Our colleagues are the key to our success as a regulator. We are committed to fostering a diverse and inclusive culture: one that’s free from discrimination and bias, celebrates difference, and supports colleagues to deliver at their best. We believe that our differences and similarities enable us to be a better organisation – one that makes better decisions, drives innovation, and delivers better regulation. 

  

If you require any adjustments due to a disability or condition, your recruiter is here to help - reach out for tailored support. 

  

We welcome diverse working styles and aim to find flexible solutions that suit both the role and individual needs, including options like part-time and job sharing where applicable. 

  

Disability Confident: our hiring approach  

We’re proud to be a Disability Confident Employer, and therefore, people or individuals with disabilities and long-term conditions who best meet the minimum criteria for a role will go through to the next stage of the recruitment process. In cases of high application volumes, we may progress applicants whose experience most closely matches the role’s key requirements. 

  

Useful information and timeline 

  • Advert Closing:  30/08/26

  • CV Review/Shortlist:  01/09/26

  • Interviews W/C: 14/09/26

  • Your Recruiter will discuss the process in detail with you during screening for the role, therefore, please make them aware if you are going to be unavailable for any date during this time.   

Skills Required

  • Extensive backend engineering experience building production services such as APIs and microservices and taking technical designs 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.
  • Experience designing, building and running reliable services in production with focus on performance, resilience and security.
  • Direct experience building and operating solutions on AWS, including AWS AI services and supporting platform services 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, and defining release and operating practices for AI services.
  • Experience leading engineering teams: providing technical guidance, aligning standards/patterns, and resolving delivery and operational challenges.
  • Demonstrable capability in prompt design and defining evaluation/testing approaches for LLM solutions (quality, safety/guardrails and performance).
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The Company
HQ: London
5,214 Employees
Year Founded: 2013

What We Do

We work to ensure financial markets work well for individuals, for businesses and for the economy as a whole. We do this by: - regulating the conduct of approximately 50,000 businesses - prudentially supervising 48,000 firms - setting specific standards for around 18,000 firms We were set up on 1 April 2013, taking over conduct and relevant prudential regulation from the Financial Services Authority (FSA). Our Head Office is based in London, and we work across the UK, from our office in Edinburgh and via colleagues in Belfast and Cardiff. Firms and individuals must be authorised or registered by us to carry out certain activities. Before we grant authorisation, firms must demonstrate that they meet a range of requirements. We then supervise these firms to make sure they continue to meet our standards and rules after they’re authorised. If firms and individuals fail to meet these standards, we have a range of enforcement powers we can use. We work alongside the Prudential Regulation Authority (PRA), the prudential regulator of around 1,500 banks, building societies, credit unions, insurers and major investment firms.

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