6 free templates across core, startup, senior, associate, enterprise, and director roles, with the disambiguation and AI-specific duties the generic template farms skip. Download as DOCX.
An AI product manager job description has one distinction the generic templates miss and one set of responsibilities they skip. The distinction: AI product manager can mean a real job (a PM who builds AI into the product) or a skill mistaken for a job (a regular PM who uses AI tools), and only the first gets a job description. The responsibilities: the AI-specific work, evaluation sets, model tradeoffs, bias and governance, that separates an AI PM from a PM with AI bolted onto the title.
At FirstHR, we build templates that draw that distinction and spell out the AI-specific duties the template farms gloss over, including an honest note on who actually hires this role. The six below cover core, startup, senior, associate, enterprise, and director versions. The guide to writing a job description covers the fundamentals.
TL;DR
An AI product manager owns AI-powered products and features: strategy, roadmap, and delivery, plus the AI-specific work of evaluation metrics, model quality and cost tradeoffs, and bias and governance. The title has two meanings, so confirm you want a PM who builds AI into the product, not a regular PM who uses AI tools. The role is almost always exempt (administrative exemption) and concentrates at tech companies, startups, and enterprise, with pay commonly $160k to $200k+. Download six versions as DOCX.
What an AI Product Manager Does
An AI product manager owns the lifecycle of AI-powered products and features, defining strategy, prioritizing the roadmap, and shipping AI capabilities while accounting for model quality, data, ethics, and feasibility. The defining feature is building AI into the product itself, working closely with data scientists and engineers.
There is no dedicated federal occupation code for the role; the nearest proxies are computer and information systems managers for senior roles and project management specialists for the PM dimension. The role concentrates at technology companies, AI startups, and enterprises adding AI to their products.
The Two Meanings of AI Product Manager
Before writing anything, resolve the ambiguity in the title, because it points to two very different things and only one of them is a job you hire for.
AI product manager (the real job)
Builds AI into the product
A product manager who owns AI-powered products or features, building AI into the product itself, accounting for model quality, data, ethics, and feasibility. This is the role that actually appears in job postings, and it is what this page is about.
AI-powered product manager (a skill, not a title)
Uses AI tools
A regular product manager who uses AI tools to work faster. This is a skill, not a separate job, so you do not write a job description for it. If this is what you mean, hire a product manager and list AI fluency as a skill.
Which One Do You Actually Need?
If you are building AI products or features, you want a real AI product manager, and the templates here fit. If you just want a strong product manager who uses AI tools well, write a regular product manager job description and list AI fluency as a skill. Posting for an AI PM when you mean the latter over-scopes and over-prices the search.
AI Product Manager Duties and Responsibilities
An AI product manager's duties cluster into four areas: strategy and roadmap, AI-specific product work, ethics and governance, and discovery and delivery. The AI-specific middle two are what set the role apart from a regular PM.
Strategy and roadmap
Own AI product strategy and roadmap
Translate needs into AI requirements
Prioritize and manage tradeoffs
AI-specific product work
Define AI quality metrics and evaluation sets
Work on model feasibility with data and engineering
The clearest way to write a strong AI PM posting is to be explicit about what this role adds on top of a regular product manager. The shared product skills are assumed; the AI-specific responsibilities are the differentiator.
Area
Regular product manager
AI product manager
Core focus
Features and user outcomes
AI-powered features plus model behavior
Quality metrics
Adoption, conversion, retention
Plus accuracy, evaluation sets, model drift
Key tradeoffs
Scope, time, cost
Plus model quality, latency, and compute cost
Risk
Product and market risk
Plus bias, safety, and AI governance
Partners
Engineering, design
Plus data scientists and ML engineers
The takeaway: a generic PM description with AI in the title attracts generalists who lack the depth. Spelling out the AI-specific responsibilities attracts the right candidates and screens out mismatches.
Which Template Should You Use?
Pick the template by level and setting: core for a mid-level PM, startup for a first product hire, senior for a product-area owner, associate for entry level, enterprise for adding AI to existing products, and director for the leadership step. Use this guide to choose.
AI Product Manager
Core, mid-level
The baseline version for a product manager who owns AI-powered products and features, with the FLSA exempt-classification note built in.
AI Startup / First PM
Founder-led, scrappy
For an AI startup making its first product hire, with the scrappy, multi-hat, build-the-function framing and equity note.
Senior AI Product Manager
Owns a product area
For an experienced PM owning a major AI product area, making high-stakes tradeoffs and mentoring others.
Associate AI PM
Entry level
For an early-career product role supporting AI products, with the non-exempt classification caution built in.
Enterprise AI PM
AI in existing products
For adding AI to an established company's products, balancing innovation with security, compliance, and scale.
Director / VP of AI Product
Senior leadership
For the leadership step that owns the AI product vision and manages the product team, with the exempt note built in.
Match the Template to the Role
Mid-level AI product owner: AI Product Manager. AI startup first hire: AI Startup / First PM. Major product area: Senior. Entry level: Associate. AI in an established product: Enterprise. Leads the product team: Director / VP. Whichever you pick, make the AI-specific duties explicit and classify as exempt.
6 Free AI Product Manager Job Description Templates
Download all six as a single Word document or copy individual templates. Each follows the same structure: company overview, position summary, key responsibilities, qualifications, a compliance note, and how to apply. Fill in the brackets, set the reporting line, and post.
Download All 6 Job Description Templates
Core, startup, senior, associate, enterprise, and director. All in one DOCX.
Template 1: AI Product Manager
The baseline version for a product manager who owns AI-powered products and features, with the FLSA exempt-classification note built in.
AI Product Manager Job Description
AI PRODUCT MANAGER JOB DESCRIPTION
Company: __ ([City, State])
Reports to: [Head of Product / VP Product / Founder]
Employment type: Full-time, W-2
FLSA status: Exempt (salaried)
Compensation: $_____ per year
ABOUT [COMPANY NAME]
[Company Name] is a [industry] company in [City, State] building AI-powered
products. We are hiring an AI Product Manager to own the strategy and delivery
of our AI features and products.
POSITION SUMMARY
The AI Product Manager owns the lifecycle of AI-powered products and features:
defining the strategy, prioritizing the roadmap, and shipping AI capabilities
while accounting for data, model performance, ethics, and feasibility. This is
a product role that builds AI into the product, not a role that simply uses AI
tools.
KEY RESPONSIBILITIES
•Own the strategy and roadmap for AI-powered products and features
•Translate user and business needs into AI product requirements
•Work with data scientists and engineers on model and feature feasibility
•Define and track AI quality metrics: accuracy, evaluation sets, drift
•Set guardrails and address model risk, bias, and AI governance
•Prioritize the roadmap and manage tradeoffs (quality, latency, cost)
•Run discovery, validate with users, and measure outcomes
•Communicate AI capabilities and limits to stakeholders
REQUIRED QUALIFICATIONS
•Product management experience, ideally with AI or data products
•Understanding of how AI and machine learning models work in products
•Familiarity with model evaluation, data ethics, and AI risk
•Strong prioritization, communication, and stakeholder skills
•Bachelor's degree or equivalent experience
COMPLIANCE NOTE (read before posting)
An AI product manager is virtually always exempt (salaried) under the FLSA,
typically the administrative exemption, since the work is directly related to
management or general business operations and involves discretion and
independent judgment. Exempt status requires meeting the salary threshold
($684 a week federally, higher in some states) and the duties test. This is
general information, not legal advice.
EEO STATEMENT
[Company Name] is an equal opportunity employer and provides reasonable
accommodations for the essential functions of this role.
COMPENSATION AND HOW TO APPLY
Compensation: $_____ per year
To apply, email __ with your resume.
Template 2: AI Product Manager (AI Startup / First PM Hire)
For an AI startup making its first product hire, with the scrappy, multi-hat, build-the-function framing and equity note.
AI Product Manager Job Description (AI Startup / First PM Hire)
AI PRODUCT MANAGER JOB DESCRIPTION (AI STARTUP / FIRST PM HIRE)
Company: __ ([City, State])
Reports to: [Founder / CEO]
Employment type: Full-time, W-2
FLSA status: Exempt (salaried)
Compensation: $_____ per year [+ equity]
ABOUT [COMPANY NAME]
[Company Name] is an AI startup in [City, State] with [number] people. We are
hiring our first product manager to own product as we scale our AI product
beyond the founding team.
POSITION SUMMARY
As our first AI Product Manager, you will build the product function from the
ground up: setting strategy, owning the roadmap, and shipping AI features fast
while bringing structure to a founder-led product. You will wear several hats
and work directly with engineering, founders, and early customers.
KEY RESPONSIBILITIES
•Own product strategy and roadmap for our AI product
•Bring structure to discovery, prioritization, and delivery
•Work hands-on with engineering to ship AI features fast
•Define AI quality metrics, evaluation, and guardrails
•Talk to customers and turn feedback into the roadmap
•Balance speed with model quality, cost, and risk
•Set up lightweight product process as the team grows
•Wear multiple hats as an early-stage startup requires
REQUIRED QUALIFICATIONS
•Product experience, ideally in AI, data, or technical products
•Comfortable owning product end to end with little structure
•Understanding of AI/ML model behavior, evaluation, and limits
•Scrappy, hands-on, and fast-moving
•Strong judgment on what to build and what to cut
COMPLIANCE NOTE
Exempt (salaried) under the FLSA, typically the administrative exemption.
Exempt status requires the salary threshold ($684 a week federally, higher in
states like California) plus the duties test. If equity is offered, describe
it accurately. This is general information, not legal advice.
COMPENSATION AND HOW TO APPLY
Compensation: $_____ per year [+ equity]
To apply, email __ with your resume.
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The compliance picture for an AI product manager is simpler than for many roles on the classification side, but the role itself carries AI-governance responsibilities worth naming. Four points belong in the hiring decision.
Almost always exempt (administrative)
An AI product manager is virtually always exempt from overtime, meaning salaried, and the usual basis is the administrative exemption. The work, owning product strategy, setting the roadmap, and making significant decisions, is directly related to the management or general business operations of the company and involves the exercise of discretion and independent judgment on matters of significance, which is exactly what the administrative exemption requires. A director or VP who manages a team can also meet the executive exemption. Given the pay levels typical for this role, the salary test is rarely the issue; the duties clearly qualify. This is general information, not legal advice.
Still confirm the salary basis
Even for a clearly exempt role, the salary basis still has to be met. The federal threshold is $684 a week, which is $35,568 a year, and several states set higher thresholds (California, for example, ties its exempt minimum to twice the state minimum wage, well above the federal figure). AI product manager salaries sit far above any of these thresholds, so the test is almost always satisfied, but the role must be paid on a true salary basis rather than docked by hours to keep the exemption intact. This is general information, not legal advice.
Watch the associate level
The one place classification deserves a second look is the associate or junior level. A genuine product role that exercises independent judgment is exempt, but an associate whose work is mostly executing defined tasks under close direction, and who earns near the threshold, could be non-exempt and owed overtime. Job titles do not determine exempt status; the actual duties and pay do. For a true associate PM with real product judgment, exempt is usually correct, but confirm rather than assume. This is general information, not legal advice.
AI governance is part of the job, not employment law
Beyond classification, an AI product manager's role itself carries responsibility for AI governance: model evaluation, bias and fairness, guardrails, data privacy, and responsible use. These are product and compliance obligations the person manages, not employment-law requirements for hiring them, but they belong in the job description because they distinguish an AI PM from a regular PM and signal that you take responsible AI seriously. Enterprise roles add data-privacy and security obligations on top. This is general information, not legal advice.
The Real Classification Question Is the Associate Level
For a mid-level or senior AI PM, exempt status is rarely in doubt: the duties clearly meet the administrative exemption and the pay clears the salary basis. The only place to look twice is an associate or junior role that mainly executes defined tasks under direction and earns near the threshold, which could be non-exempt. Classify by duties, not the title. This is general information, not legal advice.
Requirements and Qualifications
The role needs core product management skills plus a layer of AI-specific understanding, calibrated to seniority. Match the requirements to the version you are hiring.
Requirement
What to know
Product skills
Strategy, roadmap, discovery, stakeholder communication
AI understanding
How models behave, evaluation, quality metrics, tradeoffs
Governance
Data ethics, bias, guardrails, responsible AI
Technical depth
Enough to set requirements; need not build models
Education
Bachelor's common; experience and judgment matter more
Classification
Exempt for mid and senior; confirm at associate level
Keep the posting neutral and inclusive, since the EEOC prohibits job advertisements that show a preference based on protected characteristics, and the SHRM guide covers the standard sections of a job description.
How to Write an AI Product Manager Job Description
A strong AI product manager posting starts by confirming you mean the real role, picks the level, and makes the AI-specific duties explicit. Here is the process the templates are built around.
1
Confirm you mean the real role
An AI product manager builds AI into the product. If you just want a PM who uses AI tools, write a regular product manager description with AI as a skill.
2
Pick the level and setting
Core, startup, senior, associate, enterprise, or director. Pick the matching template and describe the company and product plainly.
3
Make the AI-specific duties explicit
Evaluation sets and quality metrics, model quality and cost tradeoffs, bias and governance, and partnering with data scientists, not a generic PM description.
4
Classify as exempt
An AI PM is almost always exempt under the administrative exemption. Confirm the $684-a-week salary basis and the duties test; look twice at associate roles.
5
Set pay and equity
Benchmark to seniority and market, include equity where relevant, and provide a good-faith range where pay transparency applies.
AI product managers are paid well into the six figures, reflecting the tech-company and enterprise settings where the role concentrates.
A Six-Figure, Tech-Scale Band
There is no federal wage code for AI product manager; the nearest senior proxy, computer and information systems managers, had a median wage of about $171,200 a year as of May 2024, with the highest 10 percent over $239,200 (BLS). The project-management proxy runs around $100,750.
Market estimates for AI product manager specifically commonly report average compensation in the range of roughly $160,000 to $200,000 a year, with senior and big-tech roles ranging considerably higher once equity is included, and entry-level or associate roles starting around $80,000 to $130,000. The spread reflects company stage, seniority, and equity. For a posting, benchmark to the specific seniority and your market, include equity where relevant, and provide a good-faith range where your state or city requires pay transparency. National compensation surveys are a useful reference for detail.
Hiring an AI Product Manager
The AI product manager hire turns on three things the generic templates get wrong: the title hides two different meanings, the role mostly belongs to tech companies and AI startups rather than typical small businesses, and the AI-specific responsibilities need to be explicit. Here is what actually matters.
Decide which AI product manager you mean, because the title hides two different things
The phrase AI product manager hides a distinction that trips up a lot of hiring. There is the real job, a product manager who owns AI-powered products or features and builds AI into the product itself, accounting for model quality, data, ethics, and feasibility. And there is a skill that gets confused for a job: an AI-powered product manager, meaning a regular PM who uses AI tools to work faster. Only the first generates actual job postings; the second is a capability you would list as a skill, not a separate role you write a description for. If what you need is someone to ship AI features in your product, you want a true AI product manager, and the templates here are for that. If what you need is a strong product manager who happens to use AI tools well, you should write a regular product manager job description and list AI fluency among the skills, rather than inflating the title. Getting this distinction right up front saves you from mismatched candidates and an over-scoped, over-priced search.
This is mostly a tech-company and AI-startup role, not a typical small-business hire
It is worth being honest about who actually hires AI product managers, because it shapes whether this role is right for you. The role concentrates in technology companies, AI-native startups, and larger enterprises adding AI to their products, and the pay reflects that: market data puts the average compensation well into the six figures, with senior roles ranging much higher. A non-technical small business, a law firm, an HVAC company, a local retailer, does not hire an AI product manager, because there is no AI product to manage. The realistic small-company case is narrow and specific: an AI-native startup that has grown past the founding team and is making its first product hire to bring structure to a founder-led product. That is a real scenario, and the startup template on this page is written for it, but it is a venture-backed software startup, not a typical small business. If you are not building an AI product, what you likely need is the AI developer or automation role that builds AI into your operations, not a product manager to own an AI product line.
What separates an AI PM from a regular PM is the AI-specific responsibilities, so make them explicit
The most common weakness in AI product manager postings is treating the role as a regular product manager with the letters AI bolted onto the title. The generic template farms do exactly this, producing thin descriptions that could apply to any PM. What actually distinguishes the role is a specific set of responsibilities a regular PM does not own: defining AI quality metrics and evaluation sets rather than just adoption and conversion; managing tradeoffs between model quality, latency, and compute cost on top of the usual scope-time-cost triangle; partnering with data scientists and ML engineers, not just software engineers and designers; and owning AI-specific risk such as bias, safety, guardrails, and governance. A strong AI PM understands enough about how models behave to make these calls, even without building the models themselves. Spelling out these AI-specific duties does double duty: it attracts candidates with the right depth and screens out generalists who would struggle, and it signals to everyone that your company takes responsible AI seriously. Make the AI-specific parts explicit rather than implied.
Key Takeaways
AI product manager has two meanings: a real job (a PM who builds AI into the product) and a skill (a regular PM who uses AI tools). Only the first gets a job description.
What separates an AI PM from a regular PM is the AI-specific work: evaluation sets and quality metrics, model quality and cost tradeoffs, bias and governance, and partnering with data scientists.
An AI product manager is almost always exempt under the FLSA administrative exemption; the salary basis ($684 a week federally) is easily cleared, so duties do the real work.
The one classification to look at twice is the associate level, where a junior, execution-focused role earning near the threshold could be non-exempt.
The role concentrates at tech companies, AI startups, and enterprise; pay commonly runs $160k to $200k and higher with equity, so it is not a typical small-business hire.
A small business wanting to use AI internally likely needs an AI developer or automation specialist, not a product manager to own an AI product line.
Frequently Asked Questions
What does an AI product manager do?
An AI product manager owns the lifecycle of AI-powered products and features, from strategy through delivery, while accounting for the things that make AI products different. The duties cluster into four areas: strategy and roadmap (owning AI product strategy, translating needs into AI requirements, prioritizing and managing tradeoffs), AI-specific product work (defining AI quality metrics and evaluation sets, working on model feasibility with data and engineering, managing quality, latency, and cost tradeoffs), ethics and governance (setting guardrails, addressing model risk and bias, building in responsible AI use), and discovery and delivery (running discovery, validating with users, leading cross-functional delivery, measuring outcomes). The defining feature is that an AI product manager builds AI into the product itself, working closely with data scientists and ML engineers, rather than simply using AI tools to do regular product work. The role appears mostly at technology companies, AI startups, and enterprises adding AI to their products. This page includes core, startup, senior, associate, enterprise, and director templates.
What is the difference between an AI product manager and a regular product manager?
The difference is that an AI product manager owns AI-specific responsibilities that a regular product manager does not. Both define strategy, prioritize roadmaps, run discovery, and ship products, but an AI product manager adds several layers on top. They define AI quality metrics like accuracy, evaluation sets, and model drift, not just adoption and conversion. They manage tradeoffs between model quality, latency, and compute cost alongside the usual scope, time, and cost. They own AI-specific risk, including bias, safety, guardrails, and governance. And they partner with data scientists and machine-learning engineers, not only software engineers and designers. A strong AI product manager understands enough about how models behave to make these calls, even without building the models. The distinction matters when writing the job description, because treating the role as a regular PM with AI in the title produces a thin posting that attracts generalists who lack the depth the role needs. Make the AI-specific responsibilities explicit. This is general information, not legal advice.
Is there a difference between an AI product manager and an AI-powered product manager?
Yes, and it is an important one. An AI product manager is a real job: a product manager who builds AI into the product, owning AI-powered features and the model quality, data, ethics, and feasibility that come with them. An AI-powered product manager is not a separate job at all; it describes a regular product manager who uses AI tools to work faster, which is a skill rather than a title. You write a job description for the first and hire for it as a distinct role. For the second, you would write a regular product manager job description and list AI fluency among the desired skills, since you are not hiring a different kind of person, just a PM who uses modern tools. Confusing the two leads to over-scoped, over-priced searches: companies sometimes post for an AI product manager when they actually want a capable PM who is comfortable with AI tools. Decide which you mean before you write the posting. This is general information, not legal advice.
Is an AI product manager exempt or non-exempt from overtime?
An AI product manager is virtually always exempt, meaning salaried and not entitled to overtime. The usual basis is the FLSA administrative exemption: the work of owning product strategy, setting the roadmap, and making significant product decisions is directly related to the management or general business operations of the company and involves the exercise of discretion and independent judgment on matters of significance, which is what the exemption requires. A director or VP of AI product who manages a team can also meet the executive exemption. The salary basis still has to be met, which is $684 a week federally and higher in some states, but AI product manager salaries sit far above any of these thresholds, so the duties test does the real work. The one place to look twice is the associate or junior level: a genuine product role with independent judgment is exempt, but an associate who mainly executes defined tasks under close direction and earns near the threshold could be non-exempt. Classify by actual duties, not the title. This is general information, not legal advice.
What skills should an AI product manager have?
An AI product manager needs the core product management skills plus a layer of AI-specific understanding. On the product side: strategy, roadmap prioritization, user research and discovery, stakeholder communication, and the ability to translate needs into requirements and ship. On the AI side: enough understanding of how machine-learning models and modern AI work to make sound product decisions, familiarity with model evaluation and quality metrics like accuracy and evaluation sets, awareness of data ethics, bias, and AI governance, and comfort with the tradeoffs between model quality, latency, and cost. They do not need to build or train models themselves, that is the work of data scientists and ML engineers, but they need to understand model behavior well enough to set requirements, define quality bars, and assess feasibility. Strong AI product managers also bring judgment about responsible AI use and the ability to partner credibly with technical teams. Calibrate the depth to the seniority: a senior role needs deeper technical fluency, while an associate can grow into it. This is general information, not legal advice.
Do small businesses hire AI product managers?
Rarely, and only in a specific case. The AI product manager role exists to own an AI product, so it concentrates at technology companies, AI-native startups, and larger enterprises building AI into their products, where the pay also runs well into the six figures. A typical small business without an AI product, a law firm, a contractor, a local retailer, does not hire an AI product manager, because there is nothing for the role to manage. The one realistic small-company scenario is an AI-native startup that has grown beyond its founding team and is making its first product hire to bring structure to a founder-led product; that is a venture-backed software startup rather than a typical small business, and the startup template on this page is written for it. If you run a small business that wants to use AI in your operations rather than build an AI product, what you likely need is an AI developer or an AI automation specialist who builds AI into how you work, not a product manager to own an AI product line. Match the role to whether you are building an AI product or using AI internally. This is general information, not legal advice.
How much does an AI product manager make?
AI product managers are paid well into the six figures, reflecting the technology-company and enterprise settings where the role concentrates. Market estimates vary by source and methodology, but the average total compensation is commonly reported in the range of roughly $160,000 to $200,000 a year, with senior roles ranging considerably higher, into the $300,000s and beyond at large tech companies once equity is included. Entry-level and associate roles start lower, often around $80,000 to $130,000. There is no dedicated federal wage code for AI product manager; the nearest official benchmarks are computer and information systems managers (median about $171,200 a year as of May 2024) for senior roles and project management specialists (median about $100,750) for the project-management dimension. The wide spread reflects how much the role varies by company stage, seniority, and whether equity is part of the package. For a posting, benchmark to the specific seniority and your market, include equity where relevant, and provide a good-faith range where your state or city requires pay transparency. National compensation surveys are a useful reference for detail.
What happens after I hire an AI product manager?
Run a structured onboarding so the new product manager can start driving the AI roadmap quickly. Begin with the employment basics: get the offer signed with the classification (exempt) and compensation, including any equity, clearly stated, complete Form I-9 within the first days, and gather tax forms. Then orient them to the product, the AI systems and models in use, the data, the roadmap, the metrics, and the cross-functional teams they will work with, especially data science and engineering, and make clear what they own and decide. Because AI products carry quality, cost, and governance considerations, agree early on how you measure model quality and what your responsible-AI standards are. Give them access to the product, analytics, and AI tooling they need. Store the signed offer and policy acknowledgments centrally. FirstHR supports the people side of this: an AI onboarding wizard and task workflows for a consistent checklist, e-signature for the offer and policy acknowledgments, training modules, document management for signed forms, and a simple HRIS with an org chart as the team grows. Because pricing is flat rather than per employee, a company pays one rate regardless of headcount. FirstHR does not run payroll or administer benefits, and applicant tracking is coming soon.
