AI hires, judged on what they shipped.
The market is not short on people with AI in their title. It is short on the ones who have owned a system in production. Those are the people we go and find.
From the model to the customer
We search across the full path an AI product takes: the people who build it, the people who run it, and the people who put it in front of a buyer.
AI / LLM engineers
Retrieval, agents and evaluation in production, not in a notebook.
A system they shipped, the eval that told them it worked, and what they changed after it failed.
AI architects
The person who owns the model, data and integration decisions for a product or a client.
Decisions they made under a cost or latency limit, and the trade they would make differently now.
ML engineers
Training, fine-tuning, inference and the pipelines that keep models healthy after launch.
Ownership past the first release: monitoring, drift, on-call and the cost of serving.
Forward deployed & solutions engineers
Engineers who work inside a customer's environment and ship live workflows, not demos.
Speed in an unfamiliar codebase, and the judgment to keep a human in the loop where it matters.
Data & platform engineers
The data, infrastructure and reliability work that AI systems depend on. Staff level and above.
Systems that stayed up at scale, and a clear account of the incident that taught them the most.
Go-to-market for AI platforms
Sales engineers, enterprise account executives and alliance leaders who sell AI to large buyers.
Someone who can take a CISO through model governance without waiting for backup.
Four questions every AI candidate answers
Take-home exercises tell you who has free evenings. We ask candidates to walk through real work instead.
- What did you ship, and who used it?We want a system with real users, and the candidate's own part in it.
- How did you know it worked?If they cannot name the eval, the conversation ends there.
- What broke?The answer shows whether they owned the system or only built the first version.
- What would you do differently?Senior people have a specific answer. Everyone else has a general one.
AI, data and platform searches on the board
Every role states work type and sponsorship up front. The link on each role goes straight to us, not to a portal.