AI Product Owner Jobs
AI Product Owner jobs are open across fintech, healthtech, enterprise software, and retail technology, at every level from associate to principal, with specializations in generative AI, machine learning platforms, and AI-driven product strategy. Find a role that fits from the openings below and apply directly.
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Overview Of The Role
As the Product Manager for Software / Applied AI at Lila, you will help build the first truly AI-native system of record for scientific discovery. We are looking for product leaders who can dive deep into a specific domain and own it completely. Whether your strengths align best with our core software platform or our cutting-edge agentic science offerings, you will be embedded with a dedicated scrum team to solve complex, full-stack challenges. You will sit at the intersection of commercial, engineering, design, and scientific research, building the tools that accelerate the next generation of scientific discovery. We are hiring for a wide range of function areas, and seniority levels — final title and level will be decided at the offer stage. Priority areas include 1) data, 2) ML / computational tooling, 3) scientific agents, and 4) harness & evals.
Location: Ability to work from our San Francisco, CA; or Cambridge, MA office 3-5 days per week.
Responsibilities
Deep Domain Ownership: We will match your unique product strengths to a specific scrum team, where you will go deep, define the roadmap, and become the absolute subject matter expert for that product area. That said, we operate as one product team and collaborate closely.
Full-Stack Product Execution
From designing user-facing scientific workflow tools to shaping the underlying data infrastructure that powers our AI models, you will define requirements and guide execution across the entire stack.
The Intelligence Platform For Science
Build intuitive, powerful software that scientists actually want to use. You will be responsible for translating incredibly complex scientific workflows into scalable, elegant digital products.
Cross-Functional Orchestration
Lead the dialogue between our research scientists (who push the boundaries of what's possible) and our engineering teams (who build robust, scalable systems), ensuring we ship high-impact, cohesive products.
Qualifications
Core Product Experience: Product Management experience building complex B2B SaaS, data-heavy platforms, or highly technical software products.
The Full-Stack Mindset
You are comfortable navigating both the user experience of a complex workflow and the technical realities of the backend architecture required to support it.
Bias For Action In Complexity
You thrive in ambiguous environments. You can take a vague, highly technical customer request and turn it into a clear, prioritized roadmap for your engineering team in days, not weeks.
Operational Rigor
You care deeply about the "how" — how the product is built, how it performs, and how it directly impacts the end user's daily work.
Preferred Skills
Scientific Background: A degree or deep practical experience in the hard sciences (materials science, chemistry, biology, etc.).
Building For Scientists
Direct experience building software, tools, or platforms specifically designed for scientific researchers or lab environments.
Startup DNA
Experience as an early-stage product manager who knows how to move fast, iterate, and build from 0 to 1.
Compensation
We offer competitive base compensation with bonus potential and generous early-stage equity. Your final offer will reflect your background, expertise, and expected impact.
U.S. Benefits.
Full-time U.S. employees receive a comprehensive benefits program including medical, dental, and vision coverage; employer-paid life and disability insurance; flexible time off with generous company-wide holidays; paid parental leave; an educational assistance program; commuter benefits, including bike share memberships for office-based employees; and a company subsidized lunch program.
International Benefits.
Full-time employees outside the U.S. receive a comprehensive benefits program tailored to their region. USD salary ranges apply only to U.S.-based positions; international salaries are set to local market.
Expected Base Salary Range: $180,000 USD - $288,000 USD
About LILA
Lila Sciences is building Scientific Superintelligence™ to solve humankind's greatest challenges. We believe science is the most inspiring frontier for AI. Rather than hard-coding expert knowledge into tools, LILA builds systems that can learn for themselves. LILA combines advanced AI models with proprietary AI Science Factory™ instruments into an operating system for science that executes the entire scientific method autonomously, accelerating discovery at unprecedented speed, scale, and impact across medicine, materials, and energy. Guided by our core values of truth, trust, curiosity, grit, and velocity, we move with startup speed while tackling problems of historic importance. If this sounds like an environment you'd love to work in, even if you don't meet every qualification listed above, we encourage you to apply.
We’re All In
Lila Sciences is committed to equal employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity or Veteran status. Information you provide during your application process will be handled in accordance with our Candidate Privacy Policy.
A Note to Agencies
Lila Sciences does not accept unsolicited resumes from any source other than candidates. The submission of unsolicited resumes by recruitment or staffing agencies to Lila Sciences or its employees is strictly prohibited unless contacted directly by Lila Science’s internal Talent Acquisition team. Any resume submitted by an agency in the absence of a signed agreement will automatically become the property of Lila Sciences, and Lila Sciences will not owe any referral or other fees with respect thereto.
Overview Of The Role
As the Product Manager for Software / Applied AI at Lila, you will help build the first truly AI-native system of record for scientific discovery. We are looking for product leaders who can dive deep into a specific domain and own it completely. Whether your strengths align best with our core software platform or our cutting-edge agentic science offerings, you will be embedded with a dedicated scrum team to solve complex, full-stack challenges. You will sit at the intersection of commercial, engineering, design, and scientific research, building the tools that accelerate the next generation of scientific discovery. We are hiring for a wide range of function areas, and seniority levels — final title and level will be decided at the offer stage. Priority areas include 1) data, 2) ML / computational tooling, 3) scientific agents, and 4) harness & evals.
Location: Ability to work from our San Francisco, CA; or Cambridge, MA office 3-5 days per week.
Responsibilities
Deep Domain Ownership: We will match your unique product strengths to a specific scrum team, where you will go deep, define the roadmap, and become the absolute subject matter expert for that product area. That said, we operate as one product team and collaborate closely.
Full-Stack Product Execution
From designing user-facing scientific workflow tools to shaping the underlying data infrastructure that powers our AI models, you will define requirements and guide execution across the entire stack.
The Intelligence Platform For Science
Build intuitive, powerful software that scientists actually want to use. You will be responsible for translating incredibly complex scientific workflows into scalable, elegant digital products.
Cross-Functional Orchestration
Lead the dialogue between our research scientists (who push the boundaries of what's possible) and our engineering teams (who build robust, scalable systems), ensuring we ship high-impact, cohesive products.
Qualifications
Core Product Experience: Product Management experience building complex B2B SaaS, data-heavy platforms, or highly technical software products.
The Full-Stack Mindset
You are comfortable navigating both the user experience of a complex workflow and the technical realities of the backend architecture required to support it.
Bias For Action In Complexity
You thrive in ambiguous environments. You can take a vague, highly technical customer request and turn it into a clear, prioritized roadmap for your engineering team in days, not weeks.
Operational Rigor
You care deeply about the "how" — how the product is built, how it performs, and how it directly impacts the end user's daily work.
Preferred Skills
Scientific Background: A degree or deep practical experience in the hard sciences (materials science, chemistry, biology, etc.).
Building For Scientists
Direct experience building software, tools, or platforms specifically designed for scientific researchers or lab environments.
Startup DNA
Experience as an early-stage product manager who knows how to move fast, iterate, and build from 0 to 1.
Compensation
We offer competitive base compensation with bonus potential and generous early-stage equity. Your final offer will reflect your background, expertise, and expected impact.
U.S. Benefits.
Full-time U.S. employees receive a comprehensive benefits program including medical, dental, and vision coverage; employer-paid life and disability insurance; flexible time off with generous company-wide holidays; paid parental leave; an educational assistance program; commuter benefits, including bike share memberships for office-based employees; and a company subsidized lunch program.
International Benefits.
Full-time employees outside the U.S. receive a comprehensive benefits program tailored to their region. USD salary ranges apply only to U.S.-based positions; international salaries are set to local market.
Expected Base Salary Range: $180,000 USD - $288,000 USD
About LILA
Lila Sciences is building Scientific Superintelligence™ to solve humankind's greatest challenges. We believe science is the most inspiring frontier for AI. Rather than hard-coding expert knowledge into tools, LILA builds systems that can learn for themselves. LILA combines advanced AI models with proprietary AI Science Factory™ instruments into an operating system for science that executes the entire scientific method autonomously, accelerating discovery at unprecedented speed, scale, and impact across medicine, materials, and energy. Guided by our core values of truth, trust, curiosity, grit, and velocity, we move with startup speed while tackling problems of historic importance. If this sounds like an environment you'd love to work in, even if you don't meet every qualification listed above, we encourage you to apply.
We’re All In
Lila Sciences is committed to equal employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity or Veteran status. Information you provide during your application process will be handled in accordance with our Candidate Privacy Policy.
A Note to Agencies
Lila Sciences does not accept unsolicited resumes from any source other than candidates. The submission of unsolicited resumes by recruitment or staffing agencies to Lila Sciences or its employees is strictly prohibited unless contacted directly by Lila Science’s internal Talent Acquisition team. Any resume submitted by an agency in the absence of a signed agreement will automatically become the property of Lila Sciences, and Lila Sciences will not owe any referral or other fees with respect thereto.
AI Product Owner Jobs by Experience Level
Top Cities Hiring AI Product Owners
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Find AI Product Owner JobsAI Product Owner Job Market
Who's Hiring
- Intuit18
- Google16
- Capgemini14
- Amazon14
- JPMorganChase14
Top Industries Hiring
- Technology & Software186
- Consulting & Professional Services22
- Electronics & Hardware19
- Banking & Financial Services13
- Insurance10
What Employers Look For
The qualifications that appear most often in AI product owner jobs.
- 3 or more years of product management experience in an AI or ML-driven product environment
- Ability to write and prioritize requirements for model training, evaluation, and deployment workflows
- Familiarity with machine learning concepts including model versioning, drift detection, and inference pipelines
- Experience working cross-functionally with data scientists, ML engineers, and applied research teams
- Proficiency with product discovery and roadmap tools such as Jira, Productboard, or Aha
- Bachelor's degree in computer science, engineering, data science, or a related quantitative field
Tips for Your AI Product Owner Job Search
Quantify AI product outcomes on your resume
AI product owner resumes that stand out show measurable impact: model deployment timelines, adoption rates, or reduction in manual review hours. Generic descriptions of roadmap ownership won't differentiate you when every candidate claims the same responsibilities.
Distinguish PM experience from AI product experience
Many postings screen for hands-on work with ML lifecycle tools like feature stores, model registries, or labeling pipelines. If your background is adjacent, name the specific AI systems you collaborated on, not just the product outcomes.
Apply early to roles that fit
Migrate Mate lists ai product owner openings from across the United States in one place, so you can find roles that match and apply directly to each listing.
Filter openings by technical stack requirements
AI product owner roles vary widely. Some require fluency with LLM APIs and prompt evaluation frameworks. Others focus on computer vision or recommender systems. Sorting by required tools early saves you from tailoring applications to roles that don't match your stack.
Prepare a product critique of an AI feature
Interviewers for ai product owner roles frequently ask you to critique an existing AI product decision, like a recommendation algorithm or a chatbot design. Having two or three sharp, specific critiques ready shows product judgment that generic case prep won't cover.
Negotiate for data access and compute budget
When evaluating an offer, ask directly about access to training data, annotation resources, and cloud compute budgets. These constraints shape whether your roadmap is executable, and experienced ai product owners treat them as negotiation points alongside compensation.
AI Product Owner Jobs: Frequently Asked Questions
Which companies are hiring the most ai product owners?
The companies hiring the most ai product owners right now include Intuit, Google, and Capgemini, with the largest share of openings in California, New York, and Texas, based on current listings on Migrate Mate as of August 2026. Demand is concentrated at companies actively building or scaling internal AI platforms and customer-facing AI features.
How many ai product owner jobs are remote?
About 72% of ai product owner openings are fully remote or hybrid as of August 2026, reflecting the role's strong overlap with distributed engineering and data science teams. Sub-areas focused on generative AI products and LLM integration tend to have the highest share of remote-eligible postings.
How do you become an ai product owner?
Start by building foundational product management experience, then move into roles where you collaborate directly with data scientists or ML engineers. Learn the basics of model evaluation, data labeling, and inference workflows so you can write meaningful requirements. Contributing to AI feature launches, even in a supporting role, gives you the portfolio evidence most hiring managers want to see.
Can you get hired as an ai product owner with little experience?
Yes, especially if you can show specific involvement in an AI or data product, even in a junior or associate PM role. Hiring managers often weigh a demonstrated understanding of ML tradeoffs, like precision versus recall or latency versus accuracy, more heavily than years of experience. Building a side project that uses a public API or open dataset and documenting your product decisions is a practical way to close the gap.
What does the ai product owner interview process look like?
Most processes include a recruiter screen, a hiring manager conversation focused on your AI product background, and one or two structured rounds covering product critique, technical scoping with an ML engineer, and a cross-functional collaboration scenario. Some companies add a take-home exercise asking you to define success metrics or write a requirements document for a hypothetical AI feature before the final round.
Where can I find and apply to ai product owner jobs?
You can find and apply to ai product owner jobs on Migrate Mate, which lists current openings from across the United States. Find roles that match your experience and specialization, then apply directly to each listing from the page.
See All 888+ AI Product Owner Jobs
Find roles that match your experience and apply in just a few clicks.
Find AI Product Owner Jobs