Generative AI product manager for hire

Hiring a generative AI product manager is hard for an unfair reason: the discipline is younger than most job descriptions asking for it. Résumés say "AI PM"; interviews reveal someone who once wrote a prompt. The signal that matters is whether the person has lived with a generative feature in production — watched it delight users on Monday and hallucinate on Thursday — and built the systems that manage that reality.

My production record

I co-founded WisOwl AI and shipped generative and embedding-based systems that real users depend on: a semantic matching engine built on FAISS and Supabase pgvector, and autonomous recruiter agents operating in the Indian hiring market. 5,000+ organic signups, 15+ recruiter partnerships, zero paid marketing — traction earned by output quality, because in a trust-scarce market like recruiting, one bad AI recommendation costs you the account. Underneath that: a decade of product management, including eight years at CaaStle running growth product across a $30M–$50M ARR subscription portfolio.

What a generative AI PM actually does differently

• Writes evals instead of acceptance criteria. A GenAI PRD that doesn't define the golden dataset and pass thresholds is a wish, not a spec.
• Treats variance as a design material. Where does the product show confidence? How does a user correct, retry, or escape? The failure path gets designed with the same care as the happy path — it's where trust is won or lost.
• Owns the economics. Token costs, caching strategy, and model-tier routing belong in the product decision. Features that are magical at demo scale and unprofitable at production scale are a GenAI specialty.
• Keeps the model honest about its job. Users don't want AI; they want outcomes. Half my product work is stripping generative ambition down to the narrow place it genuinely beats the alternative.

Engagement shapes: fractional (1–3 days a week running your GenAI roadmap), project-based (one feature from scoping through launch), or advisory for a founder or product lead who wants a sparring partner with production scar tissue. First step is a 30-minute call about what you're building.

Frequently asked questions

What should we look for when hiring a generative AI PM?

Ask them to describe an eval they built, a feature they killed on economics, and a failure UX they designed. Fluency in those three conversations separates production experience from prompt-tourism faster than any portfolio slide.

Fractional versus full-time for this role?

If you have one or two GenAI initiatives, fractional gets you senior judgment at a fraction of the cost, and I'll help hire the full-timer when the surface area justifies it. If AI is your entire product and you're post-Series A, hire full-time — I say that against my own interest.

Do you work directly with our engineers?

Daily — that's the job. I write specs at the level of retrieval strategy and eval thresholds, sit in the technical trade-off discussions, and I prototype myself when it's the fastest way to settle an argument.

How do you keep up with a field that changes monthly?

By building in it continuously at WisOwl — every model release gets tested against live use cases within days. Advice you get from me was validated against production traffic recently, not bookmarked from a newsletter.

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