Senior RAG Engineer

Role overview Own the retrieval systems that find reliable evidence in large collections of confidential documents and provide it to language models used in professional work. You’ll shape the full pipeline, from document processing and search to relevance checks and decisions about what an AI agent should read, with measurable accuracy as a central goal.

Responsibilities - Build and maintain document parsing, chunking, and embedding workflows. - Combine semantic search with exact-term retrieval, then rerank results for relevance. - Develop agent retrieval strategies that determine what to inspect and when there is enough evidence. - Evaluate retrieval quality with metrics and tests, including whether citations point to the right passages. - Make early architecture decisions and take ownership of their ongoing impact.

Requirements - Strong experience building retrieval or search systems for large document collections. - Knowledge of methods for evaluating search relevance, such as BM25, NDCG, or recall@k. - Ability to build search abstractions that can work across multiple backends. - Comfort working independently where priorities and processes may evolve. - Existing authorization to work in the country where you are based; visa sponsorship is not available.

Nice to have - Experience with agentic retrieval and assessing the quality of evidence passed to language models.

Benefits and work setup - Full-time, fully remote work from eligible locations in the EEA, including Norway; local employment arrangements depend on location. - Flexible, English-speaking environment with the opportunity to influence product and team practices as they develop.