Works with
Hire one when
- Your AI gives answers that sound right but cite the wrong source
- You have large, messy document collections
- Different users need to see different documents
What they do
What a RAG Engineer does for you.
Prepare documents for search: cleaning, chunking and tagging
Choose and tune embeddings and ranking
Respect permissions so people only see what they may
Measure retrieval quality on real questions
Keep the index fresh as documents change
Engineers from our own team, matched to your stack.
Start with a callHow hiring works
Four steps, no CV pile.
- 1
Intro call
What you're building, the stack and the seniority you need.
- 2
Matched engineers
We put forward engineers from our own team who fit, not a stack of CVs.
- 3
Trial week
They work on your real backlog, so you judge the work, not the interview.
- 4
Embedded
Your stand-ups, your tools, your code review. Scale up or down as you need.
Usually poor chunking, missing metadata or ranking that was never tested on real questions. Those are fixable engineering problems.
Yes, with text extraction tested on your actual files before the pipeline is built around them.
Typically within one to two weeks of scoping the role, because our engineers are already part of our delivery process.
Engineers from our own team. We do not resell freelancers from a marketplace.
Either works: you manage the work directly while we handle technical oversight, or we manage the engagement end to end.
Other roles
Build the rest of the team.
AI Agent Engineer
Agents and tool-using workflows, built for production.
LLM Engineer
LLM applications across OpenAI, Claude and open models.
Claude Developer
Products and agents built on Anthropic's Claude.
Full-Stack Engineer
React, Next.js and Node, from database to interface.
Mobile Engineer
Flutter apps for iOS and Android from one codebase.
Automation Engineer
n8n and GoHighLevel workflows that remove manual work.