£•••kAI EngineermidLondon Area, United KingdomhybridfulltimeBanking, Investment Banking, and IT System Custom Software DevelopmentPythonSQLSnowflakePower BILLMsRAGAgentic AIGitposted
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We're working with a leading banking client to recruit an AI Engineer to help deliver innovative AI, automation and data solutions in a highly regulated financial services environment. This is an exciting opportunity to join a growing technology function where you'll play a key role in transforming strategic AI initiatives into secure, scalable and measurable business solutions.
What we're looking for:
* 2+ years' experience in AI Engineering, Data Engineering, Software Engineering, Analytics Engineering, BI Development or Automation.
* Degree in Computer Science, Data Science, Software Engineering, Mathematics, Quantitative Finance or a related discipline (or equivalent commercial experience).
* Strong programming skills in Python and SQL, with experience building data pipelines, APIs, automation and analytical datasets.
* Experience working with Snowflake (or similar cloud data platforms), including data modelling, optimisation, data quality and governance.
* Knowledge of Power BI, DAX and Power Query, with the ability to create meaningful business reporting and dashboards.
* Hands-on experience with AI technologies including LLMs, prompt engineering, Python ML libraries, model evaluation, RAG and/or agentic AI frameworks.
* Understanding of the end-to-end AI delivery lifecycle, from use case identification and prototyping through to deployment, monitoring and operational support.
* Familiarity with Git/GitHub, CI/CD, testing, documentation and engineering best practices.
* Experience integrating multiple internal and external data sources via APIs, databases, files and business applications.
* Awareness of AI governance, responsible AI, data privacy, security, audit and regulatory controls.
Ideally you'll also have:
* Experience within a financial services or banking environment.
* Excellent communication skills with the ability to engage technical teams, business stakeholders and control functions.
* A pragmatic approach to delivering production-ready AI solutions that balance innovation with governance, security and operational excellence.
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