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