AI Product Owner Jobs in California

AI Product Owner jobs in California are among the most actively recruited technology roles in the country, concentrated in enterprise software, fintech, healthtech, and consumer platforms across the full range from associate product manager through director-level. San Francisco, Los Angeles, and San Diego are the primary hiring hubs, where established names like Google, Salesforce, and Qualcomm maintain large product organizations and consistently bring on ai product owners. The most in-demand specialties are generative AI product development, AI/ML platform ownership, and enterprise AI integration. Find a role that fits below and apply directly.

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Overview

Open roles306+

Top employerTikTok

Top citySan Francisco, CA

Cities hiring42

Work type44% Hybrid

Top industryTechnology

Showing 5 of 306+ AI Product Owner jobs

Product Manager, Enterprise AI

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New 22h ago

Product Manager, Enterprise AI Responsibilities:

Is the primary driver for identifying significant near and long-term opportunities in a large Product area, and driving product mission, strategies, and roadmaps in the context of broader organizational strategies and goals.
Generate buy-in and drive consensus across organizations.
Bring clarity and structure to ambiguous opportunities.
Consistently demonstrate initiative and execute with limited oversight.
Critically evaluate when AI is (and isn't) the optimal solution at portfolio level, setting the standard for rigorous tradeoff analysis.
Champion AI-native strategies including comprehensive evals and data strategies that enable org-wide continuous improvement.
Drive product development with teams of engineers and designers, while maintaining team health.
Work closely with cross-functional teams to drive product mission, define product requirements, coordinate resources from other groups (design, legal, etc.), develop roadmaps, and guide the team through key milestones.
Reimagine workflows, responsibly using AI tools to transform team velocity and capability at organizational scale.
Own Agent Core platform for Enterprise: agentic harness, orchestration, AI infra, and enterprise requirements prioritization by customer impact and blocking needs
define success, roadmap, and investment tradeoffs.
Own enterprise product readiness from pilot to scaled rollout: migration and rollout plans tracked with scorecards, privacy and compliance readiness (data retention, deletion, PII redaction, tenant isolation), and closure on reliability, auth, safety, and SLAs with engineering and field teams.
Establish evals as a first-class practice: eval harnesses, golden datasets and judges, task completion measurement driving continuous improvement.
Lead AI infra and architecture tradeoffs with engineering: orchestration, retrieval and grounding, reasoning, latency, cost, auth.
Lead cross-functional execution across Agent Core surfaces plus adjacent model, data, and go-to-market teams.
Translate AI capabilities into enterprise visions that ship to real client outcomes.
Communicate strategy and report enterprise product performance with radical clarity to clients, field teams, and leadership.

Minimum Qualifications:

Demonstrated proficiency using AI-enabled tools to build product artifacts at scale
10+ years of experience working collaboratively with engineering, design and user research teams
10+ years product management and/or Product Design
Experience developing and championing AI-native strategies across organizations
Seasoned Product Management experience shipping enterprise or platform products at scale
Experience taking a 0-1 platform from strategy through enterprise adoption and full product lifecycle
Experience turning diverse enterprise requirements and customer requests into a single coherent product strategy
Experience with agentic harness and AI infra plus LLM evals: orchestration, tool use, golden datasets and judges, task completion measurement
Technical depth with data and infra: analyze complex datasets, lead credible architecture tradeoff discussions on reasoning, latency, reliability, cost

Preferred Qualifications:

Shipped enterprise-grade AI infra or agentic products: harness, reliability, latency, security and auth, SLAs, readiness
Redesigned workflows with AI tools to measurable impact on quality or task completion
Worked with field, solutions, or partnerships teams on enterprise adoption
Demonstrated ability to integrate AI tools to optimize/redesign workflows and drive measurable impact (e.g., efficiency gains, quality improvements)
Experience adhering to and implementing responsible, ethical AI practices (e.g., risk assessment, bias mitigation, quality and accuracy reviews)
Demonstrated ongoing AI skill development (e.g., prompt/context engineering, agent orchestration) and staying current with emerging AI technologies

About Meta:

Meta builds technologies that help people connect, find communities, and grow businesses. When Facebook launched in 2004, it changed the way people connect. Apps like Messenger, Instagram and WhatsApp further empowered billions around the world. Now, Meta is moving beyond 2D screens toward immersive experiences like augmented and virtual reality to help build the next evolution in social technology. People who choose to build their careers by building with us at Meta help shape a future that will take us beyond what digital connection makes possible today—beyond the constraints of screens, the limits of distance, and even the rules of physics.

Meta is proud to be an Equal Employment Opportunity and Affirmative Action employer. We do not discriminate based upon race, religion, color, national origin, sex (including pregnancy, childbirth, or related medical conditions), sexual orientation, gender, gender identity, gender expression, transgender status, sexual stereotypes, age, status as a protected veteran, status as an individual with a disability, or other applicable legally protected characteristics. We also consider qualified applicants with criminal histories, consistent with applicable federal, state and local law. Meta participates in the E-Verify program in certain locations, as required by law. Please note that Meta may leverage artificial intelligence and machine learning technologies in connection with applications for employment.

Meta is committed to providing reasonable accommodations for candidates with disabilities in our recruiting process. If you need any assistance or accommodations due to a disability, please let us know at accommodations-ext@meta.com.

$205,000/year to $277,000/year + bonus + equity + benefits

Individual compensation is determined by skills, qualifications, experience, and location. Compensation details listed in this posting reflect the base hourly rate, monthly rate, or annual salary only, and do not include bonus, equity or sales incentives, if applicable. In addition to base compensation, Meta offers benefits. Learn more about benefits at Meta.

Product Manager, Enterprise AI Responsibilities:

Is the primary driver for identifying significant near and long-term opportunities in a large Product area, and driving product mission, strategies, and roadmaps in the context of broader organizational strategies and goals.
Generate buy-in and drive consensus across organizations.
Bring clarity and structure to ambiguous opportunities.
Consistently demonstrate initiative and execute with limited oversight.
Critically evaluate when AI is (and isn't) the optimal solution at portfolio level, setting the standard for rigorous tradeoff analysis.
Champion AI-native strategies including comprehensive evals and data strategies that enable org-wide continuous improvement.
Drive product development with teams of engineers and designers, while maintaining team health.
Work closely with cross-functional teams to drive product mission, define product requirements, coordinate resources from other groups (design, legal, etc.), develop roadmaps, and guide the team through key milestones.
Reimagine workflows, responsibly using AI tools to transform team velocity and capability at organizational scale.
Own Agent Core platform for Enterprise: agentic harness, orchestration, AI infra, and enterprise requirements prioritization by customer impact and blocking needs
define success, roadmap, and investment tradeoffs.
Own enterprise product readiness from pilot to scaled rollout: migration and rollout plans tracked with scorecards, privacy and compliance readiness (data retention, deletion, PII redaction, tenant isolation), and closure on reliability, auth, safety, and SLAs with engineering and field teams.
Establish evals as a first-class practice: eval harnesses, golden datasets and judges, task completion measurement driving continuous improvement.
Lead AI infra and architecture tradeoffs with engineering: orchestration, retrieval and grounding, reasoning, latency, cost, auth.
Lead cross-functional execution across Agent Core surfaces plus adjacent model, data, and go-to-market teams.
Translate AI capabilities into enterprise visions that ship to real client outcomes.
Communicate strategy and report enterprise product performance with radical clarity to clients, field teams, and leadership.

Minimum Qualifications:

Demonstrated proficiency using AI-enabled tools to build product artifacts at scale
10+ years of experience working collaboratively with engineering, design and user research teams
10+ years product management and/or Product Design
Experience developing and championing AI-native strategies across organizations
Seasoned Product Management experience shipping enterprise or platform products at scale
Experience taking a 0-1 platform from strategy through enterprise adoption and full product lifecycle
Experience turning diverse enterprise requirements and customer requests into a single coherent product strategy
Experience with agentic harness and AI infra plus LLM evals: orchestration, tool use, golden datasets and judges, task completion measurement
Technical depth with data and infra: analyze complex datasets, lead credible architecture tradeoff discussions on reasoning, latency, reliability, cost

Preferred Qualifications:

Shipped enterprise-grade AI infra or agentic products: harness, reliability, latency, security and auth, SLAs, readiness
Redesigned workflows with AI tools to measurable impact on quality or task completion
Worked with field, solutions, or partnerships teams on enterprise adoption
Demonstrated ability to integrate AI tools to optimize/redesign workflows and drive measurable impact (e.g., efficiency gains, quality improvements)
Experience adhering to and implementing responsible, ethical AI practices (e.g., risk assessment, bias mitigation, quality and accuracy reviews)
Demonstrated ongoing AI skill development (e.g., prompt/context engineering, agent orchestration) and staying current with emerging AI technologies

About Meta:

Meta builds technologies that help people connect, find communities, and grow businesses. When Facebook launched in 2004, it changed the way people connect. Apps like Messenger, Instagram and WhatsApp further empowered billions around the world. Now, Meta is moving beyond 2D screens toward immersive experiences like augmented and virtual reality to help build the next evolution in social technology. People who choose to build their careers by building with us at Meta help shape a future that will take us beyond what digital connection makes possible today—beyond the constraints of screens, the limits of distance, and even the rules of physics.

Meta is proud to be an Equal Employment Opportunity and Affirmative Action employer. We do not discriminate based upon race, religion, color, national origin, sex (including pregnancy, childbirth, or related medical conditions), sexual orientation, gender, gender identity, gender expression, transgender status, sexual stereotypes, age, status as a protected veteran, status as an individual with a disability, or other applicable legally protected characteristics. We also consider qualified applicants with criminal histories, consistent with applicable federal, state and local law. Meta participates in the E-Verify program in certain locations, as required by law. Please note that Meta may leverage artificial intelligence and machine learning technologies in connection with applications for employment.

Meta is committed to providing reasonable accommodations for candidates with disabilities in our recruiting process. If you need any assistance or accommodations due to a disability, please let us know at accommodations-ext@meta.com.

$205,000/year to $277,000/year + bonus + equity + benefits

Individual compensation is determined by skills, qualifications, experience, and location. Compensation details listed in this posting reflect the base hourly rate, monthly rate, or annual salary only, and do not include bonus, equity or sales incentives, if applicable. In addition to base compensation, Meta offers benefits. Learn more about benefits at Meta.

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AI Product Owner Jobs by City in California

Where California roles are concentrated, by current openings.

Santa Clara

22 jobs

Sunnyvale

20 jobs

San Diego

13 jobs

Palo Alto

11 jobs

San Mateo

8 jobs

Redwood City

8 jobs

AI Product Owner Job Market in California

A snapshot from current California openings, updated as new roles post.

Who's Hiring

TikTok23
Google16
Intuit12
Meta10
ServiceNow10

Top Industries Hiring

Technology & Software58
Electronics & Hardware4
Banking & Financial Services3
Retail2
Fintech2

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What California Employers Look For

The qualifications that appear most often in AI product owner jobs across California.

Bachelor's degree in computer science, engineering, or a related technical field required
Three or more years of product management experience with AI, ML, or data products
Demonstrated ability to write product requirements and manage an agile development backlog
Experience collaborating directly with data scientists and machine learning engineers on shipped products
Familiarity with model evaluation, responsible AI principles, and AI governance frameworks
Strong cross-functional communication skills bridging technical teams and business stakeholders

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AI Product Owner Jobs in California: Frequently Asked Questions

How do you become a ai product owner in California?

Most ai product owners in California enter through a bachelor's degree in computer science, data science, or engineering, then move into a product role after working in software engineering, data analytics, or UX. California has no state-issued license for this role. Employers treat certifications like the Certified Scrum Product Owner (CSPO) or the AIPMM Certified AI Product Manager credential as meaningful differentiators, and a portfolio of shipped AI-adjacent features carries considerable weight in the California hiring market.

Which companies hire ai product owners in California?

Employers hiring ai product owners in California right now include TikTok, Google, and Intuit, based on current listings on Migrate Mate as of September 2026. California's density of enterprise software, cloud infrastructure, and consumer technology companies means product roles at every seniority level cycle through the market throughout the year.

Which California cities have the most ai product owner jobs?

San Francisco, San Jose, and Mountain View have the most ai product owner openings in California. San Francisco's concentration of AI-native startups and major cloud platforms drives the bulk of the volume, while Los Angeles reflects growth in media technology and e-commerce, and San Diego pulls demand from its established biotech, defense technology, and wireless communications sectors.

Are there remote ai product owner jobs in California?

Yes, and more than most fields. About 67% of ai product owner openings tied to California are remote or hybrid as of September 2026, reflecting how thoroughly the role shifted during and after the pandemic. Discovery research and stakeholder interviews occasionally require in-person presence, but roadmap planning, sprint ceremonies, and cross-functional collaboration are largely conducted remotely across California's product community.

How can I get hired as a ai product owner in California with little or no experience?

The most realistic entry path is moving laterally from an adjacent role such as business analyst, software engineer, or UX researcher into an associate product manager position. Large California-based technology employers including Google and Salesforce run structured APM programs specifically designed for candidates without direct product experience. Building a public portfolio of AI product case studies and earning a Certified Scrum Product Owner credential gives early-career candidates a concrete edge when applying to California's product teams.

Where can I find and apply to ai product owner jobs in California?

You can find and apply to ai product owner jobs in California on Migrate Mate, which lists current openings tied to California employers and locations. Find roles that fit your background and apply directly to the ones that match.

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