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. 10,000+ organic jobseeker signups, 10+ recruitment-firm and startup customers, zero paid marketing. Output quality earned that traction, 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 ~$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 isn't a spec yet.
• 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, because that's where users decide whether to trust it.
• 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 care about 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 with it. At WisOwl, every model release got tested against live use cases within days, and I still prototype with new models as they ship.

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