Top AI Product Manager Jobs in Seattle, WA

Own the vision, strategy, and roadmap for MongoDB’s Partner Platform, including its Partner API, self-service onboarding, enterprise controls, billing, discovery, and partner-managed experiences. Translate partner and customer needs into scalable product capabilities, establish operating models and metrics, and collaborate across engineering, security, IAM, billing, design, marketing, and partnerships. Lead platform adoption for human and AI-agent developers while representing MongoDB externally and driving ecosystem growth.

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.

Define the vision, strategy, and roadmap for Microsoft’s Responsible AI platform. Lead development of capabilities for AI evaluation, red teaming, safety guardrails, risk detection, monitoring, governance, transparency, and compliance. Conduct enterprise customer discovery, translate emerging risks and regulations into scalable products, and coordinate execution across engineering, research, legal, security, compliance, and Microsoft product organizations. Establish success metrics, improve adoption, and represent Microsoft with customers, partners, standards bodies, and industry forums.

Lead competitive strategy for Microsoft's AI and cloud infrastructure products, evaluating accelerators, CPUs, memory, networking, storage, and rack-scale systems. Analyze technology roadmaps, performance, power, cost, supply, utilization, and total cost of ownership. Partner with architecture, engineering, finance, sourcing, and product teams to develop data-driven recommendations, competitive assessments, dashboards, and executive-level insights influencing Azure product roadmaps and investment decisions.

Lead GEICO’s IVR and conversational AI product strategy, roadmap, and lifecycle. Drive voice experience design, self-service adoption, containment, analytics, and customer satisfaction through cross-functional collaboration with engineering, design, operations, and business teams. Responsibilities include market research, feature prioritization, platform architecture influence, IVR performance optimization, analytics implementation, and integration of NLP, voice biometrics, and AI-powered intent recognition.

Lead Storyblocks’ AI product team and own the roadmap for conversational search and its MCP connector. Partner with engineering, data science, design, research, marketing, and analytics to define metrics, run experiments, conduct customer research, manage complex platform launches, and deliver business results. The role requires shipping customer-facing AI products, optimizing search and relevance, evaluating models, and communicating priorities to technical and executive stakeholders.

Own one or two client AI product engagements from kickoff through iteration. Translate ambiguous needs into requirements, backlogs, sprint plans, and evaluation criteria; manage timelines, scope, resources, and client communications; direct designers and engineers; ensure AI output quality; identify blockers; and develop repeatable AI-first delivery processes. The role requires client engagement experience, a track record of shipping AI products or features, strong communication, technical fluency, and independent ownership.

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.

Owns the roadmap, prioritization, delivery, and optimization of internal AI products supporting Revenue Operations. Partners with RevOps, engineering, data, and product teams to develop AI capabilities for forecasting, sales execution, deal governance, proposals, and enablement. Uses stakeholder research, workflow analysis, usage data, and outcome metrics to improve adoption, accuracy, productivity, process efficiency, deal quality, and revenue impact.

Own the strategy, roadmap, development, delivery, and continuous improvement of AI-powered products. Translate business and customer needs into product requirements, coordinate engineering and AI teams, define success metrics, monitor adoption and ROI, and support responsible AI governance. The role also involves stakeholder management, leadership communication, market and technology evaluation, release planning, and ensuring successful product implementation.

Leads the strategy, roadmap, development, launch, and optimization of AI-powered products. Defines product vision, requirements, priorities, success metrics, and adoption goals while coordinating engineering, AI, business, executive, and customer stakeholders. Evaluates emerging AI capabilities, supports responsible AI governance, manages product performance, and drives continuous improvement aligned with business objectives.

Leads strategy, discovery, delivery, evaluation, and continuous improvement for AI-enabled enterprise products and tools. Defines product roadmaps, user stories, KPIs, and evaluation frameworks covering reliability, accuracy, security, cost, and performance. Uses customer feedback, market analysis, and experimentation to prioritize features and validate assumptions. Partners with engineering teams, including colleagues in India, and translates complex AI concepts into scalable business value.

Own the unified roadmap for AI Transformation and Salesforce products. Lead discovery, requirements, prioritization, backlog management, delivery, adoption, and go-to-market coordination across two engineering teams. Partner with business, Legal, Security, Compliance, and Salesforce stakeholders to implement generative and agentic AI solutions, automation, and platform enhancements. Define product metrics, analyze performance, communicate strategy and trade-offs, and drive scalable products that improve employee and customer experiences.

Own an AI stockbroking product vertical end-to-end, including strategy, metrics, roadmap, technical design, delivery, regulatory requirements, AI evaluation, reliability, and launch. Partner with engineering, compliance, operations, finance, treasury, and design to build reliable financial products across payments, trading, wealth, and related services. Ensure accurate funds handling, trusted AI features, regulatory compliance, and effective execution in a distributed global team.

Own an AI neobank product vertical end-to-end, including strategy, roadmap, technical design, delivery, and launch. Partner with engineering across APIs, data flows, ledgering, reconciliation, security, and scalability. Incorporate KYC, transaction monitoring, privacy, licensing, and regulatory requirements. Apply AI with evaluation, safeguards, human oversight, and failure handling while coordinating Engineering, Design, Compliance, Operations, Treasury, and Finance.

Own an AI investing product vertical end to end, including strategy, roadmap, technical design, delivery, and launch. Partner with engineering on APIs, data flows, ledgering, reconciliation, reliability, security, and scalability. Incorporate regulatory requirements such as KYC, transaction monitoring, limits, privacy, and licensing. Apply AI with evaluation, safeguards, human oversight, and failure handling while coordinating engineering, compliance, operations, finance, and external partners.

Own the end-to-end strategy, roadmap, metrics, backlog, technical design, regulatory readiness, and launch of an AI-powered investing product. Partner with engineering, compliance, operations, treasury, finance, and design to ensure correct money movement, resilient integrations, trusted AI behavior, and compliant releases. The role requires strong technical product leadership, system design expertise, regulated-domain experience, and hands-on understanding of LLM evaluation and risk management.

Own an AI stockbroking product vertical end-to-end, from strategy and roadmap through technical design, delivery, and launch. Partner with engineering on APIs, data flows, ledgering, reconciliation, reliability, security, and scalability. Incorporate regulatory requirements including KYC, transaction monitoring, limits, privacy, and licensing. Apply AI with evaluation, safeguards, human oversight, and failure handling while coordinating Engineering, Design, Compliance, Operations, Treasury, and Finance.

Own a financial product vertical end to end, including strategy, metrics, roadmap, technical design, delivery, and launch. Partner with engineering on APIs, data flows, ledgering, reconciliation, security, scalability, and failure handling. Incorporate KYC, transaction monitoring, privacy, licensing, and other regulatory requirements. Apply AI with evaluation, safeguards, human oversight, and reliability controls while coordinating Engineering, Design, Compliance, Operations, Treasury, and Finance.

Own product strategy and multi-year roadmaps for GPU back-end networking. Translate AI workload needs into requirements, lead products through qualification and deployment, coordinate engineering and business teams, influence suppliers, and improve performance, reliability, cost, observability, and launch readiness.

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 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.

Owns an AI-focused finance product vertical end-to-end, including strategy, metrics, prioritization, technical design, regulated financial workflows, and launch readiness. Partners with engineering, compliance, operations, treasury, finance, and design to ensure accurate money movement, reliable failure handling, and trusted AI features. Requires strong system-design knowledge, experience with complex technical products in regulated domains, and hands-on judgment with LLM-based products and evaluation.

Own product areas for KIRA’s AI stockbroking and financial services applications. Define user problems, product scope, success metrics, roadmaps, and launch plans. Collaborate with engineering, design, data, operations, compliance, and business teams to simplify complex financial products. Launch features, monitor performance, use research and feedback to guide iterations, and balance speed, user experience, business impact, compliance, and operational complexity.

Own product areas for an AI-powered neobank across insurance, payments, savings, investing, travel, and other financial services. Define user problems, product scope, metrics, roadmaps, and launch plans; collaborate with engineering, design, data, operations, compliance, and business teams; simplify complex financial workflows; and use research, feedback, experiments, and performance data to drive continuous product improvements.