How do I hire AI engineers or prompt engineers as a non-technical founder in 2026?

Define the role and scorecard. 'AI engineer' and 'prompt engineer' vary widely, so list concrete must-haves for your needs: has shipped LLM features to production, builds and uses evals to measure quality, understands RAG and when to use it, and manages cost, latency, and reliability. Red flags include only demo-level work, no testing or evaluation habit, overclaiming, and inability to explain tradeoffs in plain language.

Screen without being technical. Use a small paid take-home that mirrors your actual problem and judge the result against the scorecard (does it work, is it tested, is the reasoning sound). Where you can't assess code yourself, bring in a trusted technical advisor or fractional CTO to review the submission and join one interview. Ask candidates to walk you through a past project: what they built, what broke, and how they measured success.

Pick the right model for your stage. Fractional or contract talent is ideal early when you need senior judgment for fewer hours and lower commitment; an agency can deliver a defined build but costs more and owns less context; full-time makes sense once AI is core and ongoing. For each candidate profile, audit it against your scorecard before investing interview time. The biggest mistake non-technical founders make is hiring on confident talk; insist on seeing work that actually runs.