Top AI Product Manager Jobs in San Francisco Bay Area, CA

Own the strategy, roadmap, and delivery of AI-powered capabilities across Mapbox Maps. Partner with engineering, customers, and cross-functional teams to identify use cases, prioritize development, validate solutions, and launch products. Manage pricing and packaging, sales enablement, marketing, trials, and partnerships while driving customer adoption, business growth, and scalable experiences for developers and end users.

Own the product strategy and roadmap for Glean Model Hub. Evaluate LLMs, manage model and inference-provider relationships, support customer experimentation, and oversee usage, cost, and capacity planning. Partner closely with customers and cross-functional teams to prioritize capabilities, enable adoption of new models, improve AI workflows, and build scalable processes. The role requires strong technical product management experience spanning enterprise SaaS, AI/ML operations, APIs, UX, and third-party partnerships.

Drive the development and roadmap of HPC and AI/ML products for physics, plasma, high-energy-density simulations, and resilient materials discovery. Define features, requirements, positioning, and go-to-market strategy; collaborate with engineering and NVIDIA software teams; identify customers and partnerships; and represent products at workshops and conferences.

Defines LTK’s AI product vision and strategy across agent infrastructure, LLM evaluation, machine learning models, and knowledge graphs. Partners with ML, data science, engineering, and product teams to establish model requirements, evaluation frameworks, launch criteria, and responsible AI practices. Owns trade-offs involving quality, reliability, latency, cost, privacy, transparency, and human oversight while influencing senior leaders and driving AI-powered products for creators, brands, and consumers.

Own the strategy, roadmap, and execution of Docker’s AI Gateway, enabling secure model access for developer and enterprise AI agent workflows. Responsibilities include simplifying onboarding, shaping APIs and integrations, defining governance and access controls, managing model interoperability, optimizing routing and inference costs, and driving launches. The role partners with engineering, design, customers, security stakeholders, and inference providers.

As a Sr. AI Product Manager, you'll develop growth strategies, manage customer motions, collaborate with marketing, and influence product direction based on customer insights for AIStor.

Own the AI product roadmap for document extraction, including prioritization, accuracy metrics, model and vendor decisions, capacity planning, tax-year releases, and correction workflows. Partner with AI, engineering, product, UX, QA, tax, finance, sales, and client success teams to define requirements, evaluate model performance, manage costs and latency, and deliver filing-grade structured data.

Own the strategy and outcomes for Mural’s AI Workflows products from concept through launch. Build prototypes, identify valuable collaboration workflows, define product-quality evaluations, guide model and routing decisions, and determine whether to iterate, scale, or stop based on user evidence. Partner with engineering, ML, design, finance, growth, and other teams on reliability, unit economics, data loops, and agentic multiplayer experiences.

Owns product strategy, roadmap, and execution for AI-powered experiences serving home service professionals. Responsibilities include researching workflows, defining requirements, shaping model behavior and user experiences, prioritizing roadmaps, establishing product and AI performance metrics, coordinating launches, and improving products through customer feedback and analytics. The role partners closely with Engineering, Design, Data, Marketing, Sales, Customer Success, Operations, and AI platform teams.

Designs current- and future-state workflows for AI agents across product verticals. The role facilitates discovery, translates business needs into agent-ready requirements and acceptance criteria, identifies human-in-the-loop decisions, establishes reusable workflow standards, partners with UX and engineering, and validates workflows using user feedback, evaluation results, and performance data.

Owns product development for AI-powered audit evidence review software. Responsibilities include gathering requirements, defining and prioritizing features, coordinating Design and Engineering, managing roadmaps and releases, measuring AI quality and business impact, and using product analytics to guide decisions. The role requires shipping LLM-powered features, establishing evaluation frameworks, balancing automation with human review, and delivering measurable customer and business outcomes.

Own the rollout and scale of AI agents and shared AI platform capabilities across Teamworks’ sports technology products. Drive beta-to-general-availability launches, AI-powered workflows, technical standards, integrations, evaluation datasets, regression testing, permissions, usage measurement, packaging, and customer adoption. Partner across product, engineering, and commercial teams to deliver reliable, secure AI experiences handling sensitive athlete data.

Own defined product features and workflows from discovery through launch and post-launch improvement. Create product artifacts, partner with engineering and design, incorporate customer feedback and analytics, manage roadmaps and backlogs, prepare launch plans, and monitor adoption and quality. The role requires cross-functional collaboration, benefits administration domain learning, responsible use of AI-enabled tools, and hands-on technical engagement with engineers, including troubleshooting and scripting for production support.

Lead the strategy, delivery, and continuous improvement of data and AI platforms and products. Translate business goals into requirements, user stories, backlogs, and measurable KPIs. Coordinate agile cross-functional teams, ensure quality and adoption, manage client and executive stakeholders, surface risks, and drive alignment. The role owns product workstreams within consulting engagements and requires strong data and AI platform knowledge, consulting experience, and significant end-to-end product ownership.

Own the agent orchestration platform and co-lead AI agent solutions across the insurance lifecycle. Define agent roadmaps, prompts, tools, autonomy tiers, evaluation datasets, governance, rollout gates, observability, and cost controls. Partner with product, engineering, data, and experience teams to translate business needs into agent specifications and measurable outcomes. Establish regression testing, human escalation policies, audit trails, and production quality standards for LLM-powered products.

Own enterprise product strategy and customer outcomes for Lightning AI's AI infrastructure platform. Identify high-value opportunities, translate technical user needs into product requirements, remove adoption blockers, and partner with Engineering, Sales, Customer Success, Marketing, and Design. Drive integrations, APIs, workflows, instrumentation, and enterprise expansion while coaching engineering teams and delivering intuitive products for developers.

Leads vision, strategy, and roadmap execution for Workday’s AI-powered Contract Intelligence and Analytics portfolio. Partners with engineering, data science, design, marketing, customers, and executives to develop generative and predictive AI products, define requirements, analyze markets, establish monetization strategies, and deliver enterprise SaaS solutions at scale.

Own adoption and growth of Fanatics Commerce’s internal AI platform. The role drives customer discovery, onboarding, activation, time-to-value, sustained usage, and business impact across teams. Responsibilities include identifying adoption barriers, validating AI opportunities, defining platform adoption metrics, shaping the roadmap with engineering and product partners, developing scalable adoption programs, and communicating progress and investment needs to senior leadership.

Own the end-to-end product strategy and lifecycle for AI research products, from model development and user research through launch, pricing, and go-to-market. Partner with research, engineering, design, and business teams to define requirements, ship products, analyze metrics, run experiments, and prioritize features. The role requires strong technical or quantitative foundations, product management experience, SQL and Python fluency, knowledge of machine learning, and experience taking products from zero to one.

Own the vision, roadmap, architecture, delivery, adoption, and measurement of AI-powered GTM products that improve sales productivity. Partner with sellers, GTM leaders, engineering, data, security, and business systems teams to identify workflow friction, build integrations and automations, launch prototypes and scalable solutions, and establish governance. Measure seller time savings, workflow efficiency, deal progression, adoption, and business impact while ensuring secure, reliable, trusted AI experiences.

Own the vision, roadmap, and lifecycle of Kong’s AI Management portfolio, including AI Gateway capabilities, agentic harnesses, LLM routing, policies, context, guardrails, and evaluation. Align engineering, design, marketing, and executives; translate complex AI infrastructure concepts into product requirements; manage backlogs, dependencies, technical debt, and delivery timelines; and support customer engagements and sales enablement.

Own the vision, roadmap, and delivery of customer-facing AI, predictive analytics, and SaaS data products. Partner with strategic clients, UX, data science, engineering, sales, and marketing to translate business needs into technical requirements, validate product hypotheses, and launch features that drive adoption, retention, and revenue expansion. Use SQL and data visualization tools to analyze data, communicate insights, and shape intuitive product experiences.

Own the strategy, roadmap, goals, and metrics for clinical AI products. Lead cross-functional teams of engineers, data scientists, and designers through Agile product development, from opportunity identification and requirements gathering through launch and optimization. Develop user stories and detailed specifications, analyze market and user feedback, prioritize initiatives, and build alignment across stakeholders to deliver intuitive web and mobile experiences.

The Product Manager will lead AI solution strategy and execution across the Clover ecosystem. Responsibilities include prioritizing AI workflow use cases, translating business processes into agentic experiences, defining metrics and roadmaps, building evaluation and confidence-scoring frameworks, implementing governance and audit workflows, prototyping prompts and agent systems, and partnering with vertical product managers. The role requires extensive product management experience, strong generative AI expertise, analytical execution skills, and hands-on technical prototyping capabilities.

Own the strategy and product systems for AI agents that automate complex operational workflows. Define agent reasoning, tool use, autonomy, human escalation, quality evaluation, monitoring, and continuous improvement. Work closely with customers, operators, engineers, and AI practitioners to transform messy processes into reliable products. Establish outcome-based metrics including resolution rate, accuracy, intervention rates, and time to resolution while building trust in production AI.