Artificial Intelligence Engineer

Want to build AI that actually makes a difference, rather than another proof of concept that never sees production?

We're working with an ambitious, private equity-backed financial services group that's investing heavily in AI to transform how its businesses operate.

With hundreds of advisers across the UK, they're building an AI-first technology platform designed to make complex mortgage processes faster, smarter and more efficient.

They're now looking for an AI Engineer to take ownership of the data, knowledge and retrieval systems powering their AI assistant.

This is a genuinely hands‑on opportunity where you'll have real ownership, work closely with a small innovation team and see your work used by hundreds of people across the business.

The business is developing an intelligent AI assistant that combines lender criteria, client information, business rules and historical case data to help mortgage advisers make better decisions and process cases more efficiently.

Your job is to make sure the AI has access to the right information, retrieves it accurately and continues to improve.

You'll own the journey from raw data through to the context an LLM uses to generate reliable answers.

• Building and maintaining production data pipelines using Python, SQL and APIs.
• Developing and improving LLM and RAG-based systems.
• Integrating new data sources and optimising how information is structured, indexed and retrieved.
• Building evaluation frameworks to measure AI accuracy, reliability and performance.
• Investigating inaccurate AI responses and fixing the underlying data or retrieval issues.
• Establishing data governance processes to ensure information is accurate, secure and compliant.
• Working closely with engineers, product teams and business users to drive adoption and continuous improvement.

We're particularly interested in engineers who combine strong data engineering fundamentals with genuine hands‑on experience of LLMs and retrieval systems.

You'll ideally bring:

• Strong commercial experience with Python, SQL, APIs and production data pipelines
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• Hands‑on experience building LLM / RAG solutions
  . Personal projects count if you can demonstrate what you've built.
• An understanding of embeddings, retrieval strategies, context engineering and AI evaluation.
• Experience working with cloud‑based technologies. AWS Bedrock and Lang Graph would be particularly relevant but experience of similar tools would work too.
• Strong problem‑solving skills and the ability to troubleshoot complex data and AI issues.
• The ability to communicate technical concepts clearly to non‑technical stakeholders.

Experience with in financial services, mortgages or other regulated environments would be useful, but isn't essential.

• Remote working arrangement.
• The opportunity to build and shape a production AI platform with a genuine business use case.
• Real ownership of the data and AI architecture rather than simply maintaining someone else's solution.
• Direct exposure to an ambitious innovation team with significant investment behind it.
• The chance to work on technology that will be used by hundreds of professionals.
• A business actively investing in AI as a core part of its future strategy.

If you're a Data Engineer who has moved into AI, or an AI Engineer with strong data engineering foundations, this could be an excellent next step.

You don't need to have worked in financial services. What matters is that you understand how to make LLM‑powered systems accurate, reliable and genuinely useful in production.