技术项目经理，核心产品

Own the capacity demand model, forecasting, and supply plan for a large-scale AI product area, partnering with Engineering, Data Science, Infrastructure, and Product to align roadmaps, instrumentation, and tradeoffs

Lead leadership communications for capacity: build the narratives, reviews, scorecards, and decision frameworks that give senior leadership a clear, data-grounded view of capacity health, risks, tradeoffs, and resource decisions

Drive a deep, quantitative view of AI inference capacity — modeling compute and GPU demand, and driving infrastructure efficiency and cost optimization

Build the analytical foundation — models, scorecards, and dashboards — that makes performance, efficiency, quality, cost, and capacity tradeoffs explicit and enables faster, better-grounded cross-functional decisions

Partner with Engineering to protect reliability and capacity headroom so that product growth is never limited by infrastructure, including planning for demand spikes and graceful degradation

Define and drive end-to-end program plans across multiple organizations; own risk, escalation, and change management

Establish the operating cadence — capacity reviews, planning cycles, and ramp gates — and act as the connective tissue that keeps a fast-moving, multi-team effort aligned on the right tradeoffs

Influence program and product direction across Engineering, Product, and Infrastructure through data-driven analysis and thought leadership, simplifying complexity and building alignment without direct authority

15+ years of software engineering, systems engineering, or technical product/program management experience, including owning large-scale, cross-organization technical programs

Experience delivering technical programs or products from inception to delivery jointly with Engineering, Data Science, and Product partners

Experience with capacity planning, infrastructure, or ML-serving / performance / efficiency programs at scale

Experience building quantitative models (demand, cost, capacity, or quality) and using them to inform senior-leadership decisions

Experience communicating and translating technical topics for executive and non-technical audiences, including leadership-facing narratives, reviews, and written communication

Experience influencing strategy and outcomes across multiple organizations and partners in different time zones, without direct authority

Experience gathering requirements, defining scope, and performing risk and change management on large programs

Experience owning executive communications and decision frameworks for large, cross-functional technical programs

Demonstrated ongoing AI skill development (e.g., prompt/context engineering, agent orchestration) and staying current with emerging AI technologies

Demonstrated ability to integrate AI tools to optimize/redesign workflows and drive measurable impact (e.g., efficiency gains, quality improvements)

Experience adhering to and implementing responsible, ethical AI practices (e.g., risk assessment, bias mitigation, quality and accuracy reviews)

Experience with GenAI / LLM inference at scale — inference efficiency, model right-sizing, batching, quantization, or multi-model routing

Experience with capacity and cost economics, including infrastructure cost modeling, unit economics, and ROI analysis

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in Computer Science or a related technical discipline, or equivalent experience.

15+ years of software engineering, systems engineering, or technical product/program management experience, including owning large-scale, cross-organization technical programs.