亚马逊Senior Product Manager - AI , NBS

Product Strategy & Development • Lead the development of AI-driven product strategies to drive NBS AI penetration • Identify growth opportunities across seller segments and lifecycle stages • Design and implement AI solutions that enhance seller success metrics and operational efficiency • Drive efficiency and productivity of seller recruitment, account management or go-to-market activities • Lead continuous product optimization based on user feedback Technical Leadership • Partner with data science and engineering teams to develop and implement AI/ML solutions • Define clear technical requirements and success metrics for AI-powered features • Oversee development cycles and ensure successful deployment of solutions • Drive data-informed decision making across product initiatives Stakeholder Management • Lead cross-functional collaboration between central product and program management teams, technical teams, business stakeholders, and external partners • Drive effective communication of product strategy, roadmap, and impact analysis to leadership • Manage change initiatives and stakeholder alignment across CN team and MP teams

Product Strategy & Development • Lead the development of AI-driven product strategies to drive NBS AI penetration • Identify growth opportunities across seller segments and lifecycle stages • Design and implement AI solutions that enhance seller success metrics and operational efficiency • Drive efficiency and productivity of seller recruitment, account management or go-to-market activities • Lead continuous product optimization based on user feedback Technical Leadership • Partner with data science and engineering teams to develop and implement AI/ML solutions • Define clear technical requirements and success metrics for AI-powered features • Oversee development cycles and ensure successful deployment of solutions • Drive data-informed decision making across product initiatives Stakeholder Management • Lead cross-functional collaboration between central product and program management teams, technical teams, business stakeholders, and external partners • Drive effective communication of product strategy, roadmap, and impact analysis to leadership • Manage change initiatives and stakeholder alignment across CN team and MP teams

Key Responsibilities• Lead the product and platform strategy for Researcher, Declarative Agent (DA), and GPT-5, ensuring robust, scalable, and reliable AI-powered features on mainline BizChat. • Drive deep technical and scenario-based analyses to enhance AI feature quality and relevance for global markets, with a focus on business productivity solutions. • Collaborate with science and engineering teams to build and optimize machine learning infrastructures, improving model quality, performance, and user experience. • Engage directly with customers and key partners to gather requirements, prioritize features, and foster trusted relationships across internal and external stakeholders. • Manage complex projects with clear timelines and deliverables, ensuring alignment with Microsoft’s strategic objectives for BizChat and enterprise AI solutions. • Mentor and guide cross-functional teams, promoting best practices in product management and AI development.

• Drive business impact across multiple feature areas by defining success metrics, identifying long-term investment opportunities, and aligning with Microsoft’s AI strategy. • Own the roadmap for intelligent collaboration experiences, including Copilot integrations, and lead scenario walkthroughs and golden configuration development with partner teams. • Define and deliver feature sets that balance AI innovation with fundamentals like sync reliability, performance, and accessibility; facilitate usability reviews with customers and stakeholders. • Leverage AI tools and agents to accelerate product development workflows, improve decision-making, and model best practices as an AI-native PM. • Partner with engineering, design, and marketing to build and launch features at scale, including rollout plans, customer support strategies, and internal enablement. • Engage with customer communities, MVPs, and enterprise stakeholders to build trust, gather feedback, and identify opportunities for deprecation or iteration. • Collect performance metrics and form hypotheses to improve product quality and relevance, especially in areas with complex technical or compliance requirements.