Top AI Product Manager Jobs in Seattle, WA

The Lead Product Manager will define the product strategy for AI/ML features, collaborating with engineering to deliver innovative solutions, enhancing user experiences, and bridging research with production while making critical decisions in ambiguous situations.

Leads cross-portfolio AI product strategy by integrating customer insights, pricing and packaging decisions, roadmap direction, and adoption initiatives. Partners with product, engineering, customer success, pricing, and commercial teams to shape AI platform bundles, consumption-based models, and go-to-market positioning. Establishes customer feedback programs, identifies adoption barriers, translates research into product requirements, and measures the impact of product and pricing changes on usage, expansion, and revenue.

Lead product strategy and execution for managed agent infrastructure products (e.g., harness servers, code sandboxes, action gateways). Partner with engineering and customers to define APIs, runtimes, security, observability, and scalability. Launch products, define pricing and GTM, drive adoption and business metrics, and evangelize the category to developers and stakeholders.

The Staff AI Product Manager will drive product strategy for GPU offerings, conduct market analysis, collaborate with teams for product development, and advocate for customer needs. Responsible for managing product lifecycle and utilizing data-driven approaches for product success.

Lead strategy and roadmap for AI-powered SaaS features; collaborate with engineering, data science, UX, and GTM teams to define problems, run discovery and experiments, manage backlogs, deliver product outcomes, and drive post-launch adoption and performance improvements.

Lead the strategy, development, and scaling of AI-powered products, workflows, automation tools, and decision-support systems. Own roadmaps, prioritize initiatives, define requirements and success metrics, build prototypes, evaluate AI technologies, and guide solutions through deployment and adoption. Collaborate with engineering, design, operations, stakeholders, and vendors while establishing responsible AI governance, managing risks, and measuring business impact.

The role involves defining and executing the vision for Databricks AI, collaborating with engineering teams to develop AI products, and engaging with stakeholders to uncover new use cases.

Lead product strategy and roadmaps for a unified consumer identity graph and user ecosystem. Drive signal evaluation, metrics and experiments, APIs and platform capabilities, sign-in/consent experiences, and privacy/compliance coordination across partner teams to deliver adoption and revenue impact.

Lead product development of an AI-ready data quality platform on Databricks, embedding schema enforcement, data contracts, observability, anomaly detection, CI/CD validation, and driving data product ownership, governance, and reproducibility for ML workloads.

Lead editorial direction, quality standards, and scalable evaluation frameworks for AI-powered content products across MSN and Microsoft surfaces. Partner with product, engineering, and design teams on model evaluation, prompt engineering, trust and safety, workflow improvements, and strategic planning. Drive data-informed decisions, editorial accuracy, content quality, and cross-functional execution for broad audiences.

Lead product strategy and multi-quarter roadmaps for NVIDIA’s AI Factory software-defined networking stack. Guide upstream development across OVN, OVS, and OVN-Kubernetes; define requirements, priorities, and architecture trade-offs; coordinate dependencies across DPU, fabric, virtualization, and engineering teams; and translate partner and operator needs into product releases, reference deployments, and community strategy.

Leads measurement strategy and intelligence systems for Microsoft AI monetization products. Defines KPIs, builds scalable data pipelines, dashboards, reporting, forecasting, and self-service analytics. Partners with Product, Engineering, Data Science, Finance, Marketing, and senior leaders to analyze performance, identify opportunities and risks, evaluate investments and pricing, improve data governance, and translate complex business insights into product and business decisions.

Own the enterprise AI enablement product, including its vision, roadmap, backlog, curriculum, learning paths, rollout communications, and employee champion network. Drive adoption of GenAI tools and agents among technical and non-technical employees by measuring usage, gathering feedback, and continuously improving enablement experiences. Partner with HR Learning & Development and cross-functional stakeholders while maintaining sufficient technical fluency to support rapidly changing AI capabilities.

Lead the vision, strategy, roadmap, and portfolio for AI-powered skilling products serving learners, managers, and enterprises. Partner with Design, Engineering, Marketing, content providers, and platform teams to deliver trustworthy LLM-powered experiences, measurable learning outcomes, credentials, and enterprise integrations. Drive product quality, adoption, retention, go-to-market strategy, and customer value while managing and developing Product Managers and product leaders.

Lead product strategy and roadmaps for multimedia search experiences using qualitative and quantitative research, experimentation, and cross‑functional partnership. Drive product improvements in relevance, data, UX, and measurement, manage dependencies and partner plans, and present roadmaps and results to stakeholders and executive leadership.

Own product roadmap and strategy for Databricks AI platform capabilities across training, serving, feature stores, vector search and LLM infrastructure. Partner with engineering, GTM, and customer teams to drive enterprise adoption, pricing, and commercialization of ML/AI platform features.

Own the AI product strategy and roadmap across document intelligence, workflow automation, and data-driven decisioning. Manage and mentor AI and data engineers, embed AI capabilities into the mortgage point-of-sale platform, evaluate vendors and models, and coordinate cross-functional delivery. Ship AI products from concept through production while balancing cost, quality, speed, and regulatory considerations. Establish feature prioritization processes, define product specifications, communicate tradeoffs to executives, and ensure AI systems are reliable, measurable, and aligned with customer needs.

The Data and AI Product Manager owns product vision, roadmap, backlog, requirements, prioritization, delivery cadence, success metrics, adoption, governance, and stakeholder communication. The role partners with engineering teams and business units to deliver governed data and AI products, measure business value, guide product direction, and support engineering pod leadership. It requires substantial product management experience, SQL proficiency, data platform knowledge, and the ability to translate user and business needs into actionable product decisions.

The Senior Product Manager will lead the roadmap for AI-based shopping experiences, collaborating with engineering, design, and data teams to create user-friendly AI interactions and improve product engagement metrics.

Own product areas within BJAK's AI Neobank app (insurance, payments, savings, investing, travel). Define problems, scope, metrics, roadmaps; collaborate with engineering, design, data, operations, compliance and business teams; launch features, monitor performance, iterate using data and feedback while balancing speed, UX, business impact, and compliance.

Own the strategy, roadmap, evaluation, governance, integration, launch, and lifecycle management of AI tools supporting mortgage sales. Discover Loan Officer needs, prioritize use cases, measure adoption and ROI, evaluate vendors, coordinate risk and compliance approvals, design workflows across enterprise systems, and lead enablement and change management. Partner with technical teams on integrations and internal AI builds while maintaining vendor guardrails and ensuring safe, valuable adoption.

Own the enterprise Data and AI Platform as a product, including strategy, roadmap, investment priorities, adoption, onboarding, consumer engagement, lifecycle management, governance, and value realization. Prioritize capabilities against enterprise demand, establish scalable self-service experiences, coordinate with engineering and business stakeholders, and track adoption, reuse, onboarding, coverage, and platform value metrics.

The Senior Product Manager will prioritize and deliver AI products, support cross-functional teams, enhance key metrics, and drive market leadership through innovation and research.

Oversee AI platform product development from ideation to launch, collaborate with cross-functional teams, and ensure successful product management.

Own the AI and data product roadmap, prioritize and sequence development with engineering and founders, ship trustworthy AI experiences, drive adoption, define feature success metrics, evaluate outcomes, and manage the analytics foundation. The role requires technical fluency in AI, prior software engineering experience, production AI product delivery, strong product judgment, and comfort working in a fast-paced, remote startup environment.