Senior RAG Engineer

iFindTech

9d • Remote

About The Position

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.

Requirements

• 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

Responsibilities

• Own the retrieval layer of the production AI platform, including document ingestion, chunking, and embeddings.
• Implement and manage hybrid search, reranking, and evaluation processes.
• Develop and optimize agentic retrieval systems.
• Ensure accurate and reliable information retrieval at scale.
• Influence architecture and technical direction of AI systems.
• Diagnose and improve retrieval performance in production.

What This Job Offers

• Job Type: Full-time
• Career Level: Senior
• Education Level: No Education Listed