亚马逊AI Product Manager, Amazon Global Selling

Define AI product vision and strategy across Global Selling seller segments and lifecycle stages; identify high-impact opportunities to apply AI/ML (e.g., GenAI, agentic AI, intelligent automation) to empower business teams — including Marketing, CRM, seller acquisition, and seller growth — to drive operational efficiency and business outcomes at scale. Own the end-to-end AI product lifecycle — from ideation and opportunity sizing, through technical development and experimentation, to launch, adoption, and iterative improvement — ensuring alignment between business objectives, user needs, and technological capabilities. Develop and communicate product requirements including model objectives, data specifications, evaluation metrics, and responsible AI guardrails; earn trust from cross-functional stakeholders (engineering, applied science, design, business operations) and external partners through clear documentation and aligned decision-making. Lead cross-functional and cross-regional collaboration with scientists, engineering, and data teams to build, evaluate, and ship AI-powered products; drive development velocity by managing trade-offs, unblocking technical dependencies, resolving issues, and maintaining rigorous experimentation standards (A/B testing, model performance benchmarks). Drive measurable business impact post-launch through continuous monitoring, data-driven iteration, and feedback loops; leverage market analysis and competitive intelligence to inform product positioning and roadmap evolution. Manage stakeholder and leadership communications across multiple geographies — including problem framing, AI solution trade-off analysis, product/business reviews, budget and headcount planning, and organizational change management for AI adoption at scale. Partner with international stakeholders, leaders, and tech teams to align priorities and drive execution across regions.

* Identify opportunities across the Global Selling Seller segments and lifecycle, define product strategy and proposition, build up new products/services to help seller growth and AM’s workflow optimization, and continuously drive product success post launch. * Clearly define and communicate product requirements, collaborate with and earn trust from internal stakeholders and external partners, and design and align system solutions. * Work with technology teams to develop products, resolve issues and manage development cycles * Manage stakeholder and leadership communications including problem statement and analysis, product solution review, business/impact review, budget/HC planning, stakeholder change management, etc.

1. 电路设计AI智能体产品规划与交付：主导电路设计AI智能体的产品规划与交付，深入理解原理图、Layout、仿真等环节，将设计需求转化为智能体能力，建立评估体系并驱动迭代； 2. 数据底座产品架构定义：定义数据底座产品架构，打通EDA工具链、PLM与ERP及设计文档的数据孤岛，建立统一元数据标准； 3. 电路设计场景AI应用孵化：扫描电路设计全链路痛点，识别智能选型、原理图审查、设计复用推荐等高价值AI介入机会，主导概念验证与产品落地； 4. 技术追踪与路线图制定：追踪主流大模型技术演进，建立面向电路设计场景的模型选型框架，制定产品Roadmap，协同多团队推进落地。

1. 高价值AI机会识别与产品转化：深入企业财务、销售、采购领域业务，识别AI可解的高价值问题空间，负责将其转化为产品； 2. AI产品全生命周期管理：管理AI产品全生命周期的各个阶段，包括需求收集和洞察、产品规划、设计、开发、测试和发布等； 3. 目标定义与指标跟踪：定义产品目标和核心指标，持续跟踪指标以进行产品增强，并清晰地向用户阐述每个功能的价值； 4. 技术趋势跟踪与标杆研究：持续跟踪AI在制造业的应用趋势与前沿技术，研究竞品与标杆案例，沉淀产品方法论及实践经验，并可落实到具体业务场景； 5. 产品运营推广支持：支持产品运营推广，输出产品操作手册、培训材料、产品定位、运营策略，协助业务团队完成产品的快速应用。