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Zof AI

Technical Product Manager

northern, KY

Check who can apply and the requirements below before continuing.

About this opportunity

Zof AI lists this Technical Product Manager opportunity in northern, Kentucky. Review the employer’s description below for duties, qualifications and application requirements.

Job description

Zof AI is seeking a Technical Product Manager to own product decisions where model behavior meets business value. This role owns the trade-offs that define AI products: cost versus quality versus latency, what to automate versus verify, and what "good enough to ship" means, backed by evals rather than intuition. The ideal candidate has shipped AI-powered products, communicates precisely, and can hold both customer outcomes and model realities in view at once.

Product · Senior · Full-time · On-site · San Francisco, CA

Responsibilities

Own product direction for AI features from problem to shipped outcome.

Own the cost, quality, and latency trade-offs of AI capabilities.

Define what "working" means and back it with evals, not intuition.

Translate customer and market needs into a credible product roadmap.

Partner with engineering on what to build, buy, or call an API for.

Prioritize ruthlessly in a small, fast-moving team.

Communicate product decisions clearly to the team and customers.

Measure adoption and outcomes, and iterate on evidence.

Requirements

Experience shipping AI or ML-powered products.

Working understanding of model capabilities, limits, and economics.

Strong product judgment and prioritization.

Ability to reason about quality metrics and evaluation.

Excellent written and verbal communication.

Comfort operating hands-on in an early-stage environment.

High ownership and follow-through.

Willingness to use AI tools deeply in day-to-day work.

Nice to have

Technical background or ability to read code and technical docs.

Experience with developer tools, QA, or enterprise software.

Experience taking an early product to market.

Experience working directly with enterprise customers.

Must understand model capabilities and own cost, quality, and latency trade-offs as product decisions

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Who can apply

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