Senior RAG Engineer

We’re working with a fast-growing AI company looking for a Senior Retrieval / RAG Engineer to take ownership of the retrieval layer at the heart of its production AI platform. You’ll own everything from document ingestion, chunking and embeddings through to hybrid search, reranking, evaluation and agentic retrieval. This is a highly hands-on role where you’ll have real influence over architecture and technical direction, building AI systems that need to retrieve the right information accurately and reliably at scale. Fully remote anywhere within the EU.

Must Haves

5+ years of production backend engineering experience

2+ years building and operating RAG / retrieval systems in production

Strong Python experience

FastAPI or similar production Python frameworks

Production experience with vector databases such as Qdrant, Pinecone, Weaviate or similar

Strong understanding of embeddings, semantic search, hybrid retrieval and reranking

Experience evaluating retrieval quality using metrics such as Recall@K and NDCG

PostgreSQL / SQL

Experience diagnosing and improving retrieval performance in production

Comfortable taking genuine end-to-end ownership

Nice to Haves

Agentic retrieval and multi-step search workflows

Query decomposition

BM25 / information retrieval experience

Golden datasets and retrieval regression testing

Large-scale or OCR-heavy document ingestion

Redis and background processing

Multi-tenant architectures and data isolation

Multilingual retrieval/search

Experience benchmarking different embedding models, vector databases or LLM approaches

Experience using AI coding tools such as Claude Code, Copilot or similar