Senior AI Engineer

Purpose of the role

Where the Senior Data Scientist leans toward pricing and modelling depth, this role is deliberately broader: building agents, RAG pipelines and integrations end to end, and moving fluidly between model work, tooling and delivery as the project needs. It also contributes to making LLM behaviour reliable and measurable, but as a generalist rather than a pricing/modelling specialist.

Key responsibilities

•    Design, build and ship agents end to end — from prompt/tooling design through RAG pipeline construction to integration with production systems.

•    Build and maintain RAG pipelines and integrations across a range of data sources and services.

•    Design evaluation metrics and evaluation loops for LLM agents, in collaboration with the Senior Data Scientist.

•    Contribute to converting non-deterministic LLM solutions into deterministic, trustworthy ones through structured evaluation and guardrails.

•    Move between model development, tooling/integration work and hands-on delivery as project priorities shift — this role is intentionally less specialised than the Senior Data Scientist.

•    Build and integrate MCP-based tools and services to extend agent capability.

•    Build monitoring/evaluation dashboards in code.

•    Apply reinforcement learning techniques to model development where relevant.