AI Product Engineer Jobs in California

AI Product Engineer jobs in California are among the most active in the country, concentrated in tech, fintech, enterprise software, and consumer AI across a seniority range from junior associate to principal engineer. The largest hiring metros are San Francisco, Los Angeles, and San Diego, where companies like Google, Apple, and Salesforce maintain major engineering operations and consistently recruit for this role. In-demand specializations include LLM-based product development, AI infrastructure tooling, and cross-functional product management with ML systems expertise. Find a role that fits below and apply directly.

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Overview

Open roles330+

Top employerTikTok

Top citySan Francisco, CA

Cities hiring47

Work type43% Hybrid

Top industryTechnology

Showing 5 of 330+ AI Product Engineer jobs

Product Manager, Enterprise AI

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Added 1d 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 Engineer Jobs by City in California

Where California roles are concentrated, by current openings.

Sunnyvale

21 jobs

San Diego

13 jobs

Palo Alto

12 jobs

Los Angeles

10 jobs

Cupertino

8 jobs

AI Product Engineer Job Market in California

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

Who's Hiring

TikTok23
Google17
Intuit12
Meta10
ServiceNow10

Top Industries Hiring

Technology & Software59
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 engineer jobs across California.

Bachelor's or master's degree in computer science, AI, or a related engineering field
Demonstrated experience building and shipping AI or ML-powered product features
Proficiency with Python and machine learning frameworks such as PyTorch or TensorFlow
Experience working cross-functionally with data science, design, and engineering teams
Familiarity with LLM APIs, prompt engineering, or retrieval-augmented generation pipelines
Strong product sense with the ability to translate user needs into AI-driven solutions

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AI Product Engineer Jobs in California: Frequently Asked Questions

How do you become a ai product engineer in California?

Most ai product engineers in California start with a bachelor's or master's degree in computer science, artificial intelligence, or software engineering, as no state-issued license is required for this role. California employers, especially in the Bay Area and Los Angeles tech corridors, typically expect hands-on ML or product experience alongside a degree. Building a portfolio of AI-driven product work, contributing to open-source projects, or completing graduate programs at UC Berkeley, UCLA, or Stanford strengthens a candidate's profile considerably.

Which companies hire ai product engineers in California?

Employers hiring ai product engineers in California right now include TikTok, Google, and Intuit, based on current listings on Migrate Mate as of September 2026. California's concentration of AI-native companies and large tech headquarters means demand is spread across both early-stage startups in the Bay Area and established enterprise organizations in Los Angeles and San Diego.

Which California cities have the most ai product engineer jobs?

San Francisco, San Jose, and Mountain View have the most ai product engineer openings in California, reflecting the state's geography of tech employment. San Francisco and the broader Bay Area lead because of the density of AI-focused companies and major tech headquarters there, while Los Angeles has grown into a significant hub driven by its consumer tech, media-tech, and fintech sectors, and San Diego draws demand from its biotech and defense-adjacent software companies.

Are there remote ai product engineer jobs in California?

Yes, and more than most fields. About 65% of ai product engineer openings tied to California are remote or hybrid as of September 2026, reflecting how well this role translates to distributed work environments. Product and engineering collaboration tasks, including design sprints, code reviews, and model evaluation, are well suited to remote settings, though roles requiring close integration with on-site infrastructure or hardware teams tend to stay in-person.

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

The most realistic entry path is moving from an adjacent role, such as software engineer, data analyst, or technical product manager, into AI product work by demonstrating applied ML skills through side projects or internal initiatives. Large California employers including Google, Meta, and Salesforce run new-grad programs and associate product manager rotations that explicitly recruit candidates without prior AI product experience. Building a public portfolio using open-source LLM tools and contributing to AI product communities active in the Bay Area accelerates candidacy considerably.

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

You can find and apply to ai product engineer jobs in California on Migrate Mate, which lists current openings tied to California employers. Search the available roles, find the ones that match your experience and preferences, and apply directly to the ones that fit.

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