Hire AI engineers without a six-month hiring round
Engineers who have actually shipped AI to production — agents, retrieval, evaluation — embedded into your team, or owning a workstream end to end.
- Team of 12
- India-based
- NDA before discovery
one of your team from week one
- Starts inside your process, not beside it
- Code and models stay yours
- Hire them permanently later if it works
Specialisms you can bring in
AI engineering has split into genuinely distinct skill sets. Hiring for the wrong one is a common and expensive mistake, so we would rather match the specialism to the problem than send a generalist.
AI Application Engineer
Builds AI features into products — retrieval, structured outputs, guardrails, and the application code around them.
AI Agent Engineer
Designs and builds tool-using agents with permission boundaries, approval gates, and full traceability.
RAG / Retrieval Engineer
Owns document ingestion, chunking, hybrid retrieval, reranking, and permission-aware search over your corpus.
LLM Evaluation Engineer
Builds the eval sets, scoring, and CI gates that tell you whether an AI feature is getting better or worse.
AI-Native Full-Stack Engineer
Ships product features using AI-assisted development under review — faster delivery without dropping the quality bar.
Prompt & Context Engineer
Works on prompt architecture, context assembly, and output reliability for features already in production.
Three ways to work with us
Embedded engineer
One or more engineers working inside your team, your sprints, and your tooling. You direct the work day to day.
Best when
You have a team and a roadmap, and need AI capability you cannot hire quickly enough.
AI squad
A small self-directing group — engineering plus review — that owns an AI workstream end to end.
Best when
You want an AI capability delivered, not managed. We own the outcome.
Fractional AI lead
Senior direction part-time: architecture, model and tooling choices, evaluation strategy, and reviewing your team's AI work.
Best when
Your engineers are capable but nobody has done this before and the decisions are piling up.
From enquiry to first commit
- 01
Scope the requirement
A call to understand the problem, not just the job title. This is usually where the specialism gets corrected.
- 02
Match and introduce
We propose named engineers with real backgrounds and you interview them. No anonymous resource pools.
- 03
Agree terms
Engagement model, overlap hours, IP assignment, and NDA signed before work starts.
- 04
Onboard and ship
Access, context, and a first deliverable inside the initial sprint rather than a ramp-up month.
Included as standard
- Senior engineering review on all work, regardless of who directs it
- Full IP assignment — code, prompts, and eval sets are yours
- NDA executed before any discovery conversation
- Direct communication with the engineer, not through an account manager
- Agreed timezone overlap stated in the contract
- Documented handover if the engagement ends
Questions we get asked
01How quickly can an engineer start?
Typically within one to two weeks for a single engineer, depending on the specialism. Larger squads take longer to assemble. We would rather tell you a real date than promise immediate availability and then substitute whoever is free.
02Do engineers work in our timezone?
We work from India and maintain deliberate overlap with your working hours. Full overlap with US Pacific is not realistic, so we agree the overlap window up front and structure handovers around it rather than pretending the gap does not exist.
03What is the minimum engagement?
One month for embedded engineers, though most engagements run longer because context takes time to build and is wasted if it walks out early. Fractional leadership can be as little as a few days a month.
04Who owns the code and the models?
You do. Code, prompts, eval sets, and any fine-tuned artefacts produced during the engagement are yours, assigned on delivery. We sign NDAs before starting.
05Can we hire the engineer permanently later?
It is worth discussing rather than being blocked. We would rather agree terms for that in the contract at the start than have it become an awkward conversation later.
06How do you make sure quality holds?
Every engineer works under senior review, and AI-generated code passes the same gates as anything else — human review, automated tests, and security checks. That is a standard we hold regardless of who is directing the work.
Tell us what you are trying to build.
Describe the problem rather than the job spec — the right specialism usually becomes obvious once we understand what the AI actually has to do.