Senior Product Manager, Tech, Amazon Manufacturing Services

Amazon Manufacturing Services (AMS) is seeking a Sr. Product Manager, Tech to own the product vision, strategy, and roadmap for the manufacturing execution and automation intelligence stack powering Amazon’s first advanced manufacturing facility — a highly automated, first-of-its-kind operation. This facility integrates industrial robotics, end-to-end manufacturing automation, and digital manufacturing to produce systems for Amazon’s global fulfillment network. Key job responsibilities Manufacturing Execution Product Strategy • Own the 2–3 year product roadmap for the manufacturing execution stack — from scheduling UX through operator tools to AI-powered optimization • Define the product vision that connects AI-native scheduling intelligence to the physical shop floor experience • Develop and maintain the execution technology strategy across P0 (manual + semi-automated), P1 (AGV integration, real-time optimization), and P2 (AI-enabled autonomous control) • Write compelling narratives (PR/FAQs, 6-pagers, OP docs) that articulate product strategy and secure investment from leadership Scheduling & Operator Experience • Serve as the operational product partner to the scheduling engineering team — translating manufacturing floor needs, pain points, and workflows into product requirements • Own the operator-facing scheduling experience: how assignments surface, how disruptions are communicated, how overrides are captured, and how the system explains its decisions to the right audience • Drive the scheduling system’s authority progression (Shadow → Advisory → Co-Pilot → Decision Maker) by defining success criteria, measuring override rates, and building supervisor trust through UX design • Define product requirements for scheduling and explainability tools from the operator/supervisor perspective Machine Connectivity & IIoT • Own the product vision for machine connectivity — defining how equipment telemetry flows from factory floor to data lake to decision systems • Define integration requirements for manufacturing equipment onboarded at the manufacturing facility (industrial lasers, robotic welding cells, automated coating lines, autonomous mobile robots) • Develop product requirements for digital twin capabilities — real-time equipment state, simulation for what-if analysis, and predictive modeling • Partner with automation engineers to define the machine-to-cloud data contract for each equipment class AI/ML & Continuous Improvement • Define and execute product strategy for AI-driven manufacturing intelligence: predictive maintenance, automated quality inspection, process parameter optimization, and autonomous cell control • Own requirements for the data platform layer that enables ML — feature stores, event streams, model serving infrastructure • Drive the feedback loop between quality outcomes (first-pass yield, scrap rates) and upstream process adjustments — ensuring the system learns and improves continuously • Define the operator interaction model for AI recommendations — when to alert, when to auto-act, when to require human confirmation Shop Floor Quality & Compliance • Own the product experience for in-line quality: inspection workflows, non-conformance reporting, root cause analysis tools, and SPC dashboards • Define how quality data flows back to both the scheduling system (for replan triggers) and the enterprise system (for financial variance reporting) • Partner with Quality Engineering to translate ISO 9001:2015 requirements into tool capabilities and audit-ready data records A day in the life In the morning, you review overnight production data from our prototyping factory — the scheduling system’s override rate dropped to 7% this week, and you’re preparing the case to promote it from Shadow to Advisory mode. You pull the override-reason breakdown to identify two UX issues driving unnecessary supervisor interventions, then draft requirements