Jobs in Oslo, Norway

About the role

You'll own retrieval. When someone asks our product a question, something has to find the right passage across large sets of confidential documents, decide it really is the right passage, and hand it to a language model whose answer ends up in real professional advice. That whole path is yours: how documents get parsed, chunked and embedded, how search combines meaning with exact terms, how results get reranked, and how an agent decides what to read next and when it has read enough. This is where AI products fail without anyone noticing. The answer reads well, the citation is wrong, and the client is the one who finds out. It isn't CRUD work, and it isn't a demo notebook either. Retrieval is where AI products quietly fail: the answer reads well, the citation is wrong, and nobody notices until a client does. Your job is to stop that happening, and to be able to show with numbers that it isn't happening. You'll make architecture calls early and live with them. The role is fully remote. Work from anywhere in the EU.

What you'll bring

• At least five years building backend systems that run in production, and at least two of them shipping retrieval or RAG systems real users depend on.
• Backend depth without production retrieval won't be enough for this role, but our Senior Backend Engineer role might be the better fit.
• You've diagnosed a retrieval regression in production and fixed it.
• You can tell us what broke, how you found it, and what the numbers were before and after. - You've built and maintained a golden set.
• How many queries, who labelled them, which metrics you trust, and a change you shipped or killed because of what they told you.
• You've run a vector index in production: picked index parameters, dealt with the memory and latency trade-offs, and reindexed without taking search down.
• Strong Python.
• Comfortable reasoning about FastAPI or a close equivalent, PostgreSQL and Redis under load.
• You don't ship a retrieval change because the output looked better on the three queries you tried by hand.
• You own things end to end — including the boring maintenance and the tech debt nobody assigned you — rather than building the interesting part and handing off the rest.
• You track what's moving in vector databases and LLMs because you're curious, not because it's the job.
• Show us the side project, the benchmark you ran for fun, or the repo where you tried something before it showed up in everyone else's stack.