Senior AI Engineer

We are looking for a Senior AI Engineer to join our team and take ownership of key areas within our technology and data platform. Owns the AI layer: retrieval, agents, and natural language interfaces over enterprise data, with evaluation so quality is measured rather than demonstrated.

Key Responsibilities

• Own and deliver solutions within the scope of the role, from requirements and technical/design decisions through implementation and continuous improvement.

• Work closely with engineering, product, data, design, and business stakeholders to translate requirements into practical, scalable solutions.

• Apply strong engineering and/or domain expertise to build reliable, maintainable, and production-ready capabilities.

• Contribute to architecture, standards, documentation, quality, and technical decision-making appropriate to the role.

• Identify performance, scalability, data quality, usability, reliability, or operational risks and address them proactively.

• Collaborate across teams to ensure solutions integrate effectively with existing systems and platform components.

• Experience: 5+ years of relevant professional experience.

• Strong hands-on experience with: LLM application engineering, RAG and retrieval architecture, embeddings and vector search, agent and tool calling systems, LLM evaluation, Python.

• Software or data engineering background, with at least two years building LLM based systems that reached production.

• Retrieval architecture: chunking, embeddings, vector and hybrid search, and why naive RAG fails on structured data.

• Agent or tool calling systems, including permissions, scoping, and guardrails.

• Evaluation practice: test sets, regression suites, hallucination and grounding checks.

• Comfortable working inside a data platform rather than calling a hosted API.

Preferred Qualifications

• Self hosted open weight model serving with vLLM or equivalent, inference optimisation, and GPU resource management.

• Fine tuning or adaptation of open weight models.

• Text to SQL or semantic layer work over a real data model.