This free AI Product Manager job description template is ready to use — copy it, replace the {{placeholders}}, and post your role in minutes. It includes a company intro, a role summary, responsibilities, requirements, nice-to-haves, and compensation, with writing tips and FAQs below to help you tailor it to your team.
When to use this template
Use this when you're hiring a product manager to own AI-powered features — someone who understands both product fundamentals and the particular challenges of building with models: non-determinism, evaluation, cost, and trust.
AI PM candidates want to know how central AI is to the product, how mature the work is, and how technical the role expects them to be. Be specific, because building with models is meaningfully different from traditional PM work.
If the role is general product management, use the Product Manager template instead.
Writing tips
- Describe the AI features they'll own and how central AI is to the product.
- Emphasize the unique challenges: non-determinism, evaluation, cost, and trust.
- Clarify how technical the role expects the PM to be.
- Distinguish from a general product management role.
- Include the salary range and reporting line.
The job description
Copy the template below and replace the {{placeholders}} and [bracketed notes] with your specifics.
About {{company}}
{{company}} is [what you do]. We're building [AI product/area], and we're hiring an AI Product Manager to own it end to end.
The role
As an AI Product Manager, you'll own AI-powered features from discovery to launch — understanding users, shaping the roadmap, and navigating the realities of building with models: evaluation, non-determinism, cost, and trust. This role reports to {{hiring_manager}} and is based {{work_type}} in {{location}}.
What you'll do
- Own the roadmap for [AI feature / area] and the outcomes it drives.
- Define what 'good' looks like and how to evaluate AI output quality.
- Partner with AI engineers and data scientists to ship reliable features.
- Balance capability, cost, latency, and trust in product decisions.
- Talk to users and use data to find the highest-impact AI opportunities.
What we're looking for
- 3+ years of product management shipping software products.
- A strong grasp of how modern AI works and where it breaks.
- Comfort defining and using evaluations to judge quality.
- Fluency with data and the judgment to make calls amid uncertainty.
- Excellent communication across technical and non-technical teams.
Nice to have
- Experience shipping AI or ML features in production.
- A technical background or comfort going deep with engineers.
- Familiarity with LLMs, RAG, and evaluation.
What we offer
- Salary range: {{salary_range}}, plus equity.
- [Comprehensive benefits].
- Flexible {{work_type}} working and [PTO policy].
- Ownership of AI products at a company that's serious about them.
How to personalize
Replace these placeholders before posting:
- {{company}}
- {{location}}
- {{work_type}}
- {{salary_range}}
- {{hiring_manager}}
The bracketed notes — like [your benefits] or [your primary language(s)] — are prompts to swap in your own details. The more specific you are about the actual work and stack, the stronger your applicant pool will be.
Frequently asked questions
- What does an AI Product Manager do?
- An AI Product Manager owns AI-powered features end to end — researching users, shaping the roadmap, and shipping with engineering and data science. Beyond standard PM work, they navigate the realities of building with models: defining evaluations, and balancing quality, non-determinism, cost, and trust.
- What's the difference between an AI Product Manager and a Product Manager?
- Both own products end to end, but an AI Product Manager specializes in the unique challenges of building with models — evaluation, non-deterministic output, cost and latency trade-offs, and user trust. It requires a stronger grasp of how AI works and where it fails.
- What skills should an AI Product Manager have?
- Strong product fundamentals, a solid grasp of how modern AI works and where it breaks, comfort defining and using evaluations, fluency with data, and the judgment to decide amid uncertainty. Experience shipping AI features and a technical bent are valuable pluses.