"Hiring an AI engineer: questions that separate builders from demo-makers"
Every CV now says "LLM experience", and a polished demo tells you almost nothing about whether someone can ship a system that survives production. The questions that actually discriminate are about evals, failure modes and cost controls — not model names.
Every CV that crosses your desk now says "LLM experience". Every candidate has a demo. And if you are a founder or CTO hiring your first AI engineer — staff or contract — you have a real problem: the skills that make a demo and the skills that make a production system look identical in a portfolio and are completely different in practice. I have spent about ten years shipping software, the last few shipping AI systems, and I sit on both sides of this — I sell this work, and I have watched others sell it badly. Here are the questions I would ask.
Have an AI feature stuck between demo and production?
The gap — reliability, evals, cost control, the plumbing that keeps it running unattended — is exactly the work I do. If that sounds familiar, a short conversation is usually enough to point you the right way.
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