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 Amazons 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 Amazons global fulfillment network.

Key job responsibilities
Manufacturing Execution Product Strategy
Own the 23 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 systems 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 systems override rate dropped to 7% this week and youre 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 for the engineering team.

Mid-morning you join the scaled factory equipment onboarding review. The laser cutting integration team needs a decision on telemetry frequency you work through the tradeoffs between data granularity (better for predictive maintenance models) and network cost (lower in batch mode) landing on a tiered approach by signal type.

After lunch youre on the prototype factory floor shadowing a powder coating operator through a disruption scenario a rush order just reshuffled the queue and you observe how the shop floor app communicates the change. The operator missed the notification; you sketch a design change in your notebook.

You close the day reviewing the ECO blast-radius prototype with the engineering team. An engineering change landed that affects 47 in-flight orders the impact visualization needs to surface at-risk-dollars more prominently for the Change Control Boards decision meeting tomorrow.

- Bachelors degree or above in Computer Science Engineering or related fields
- 7 years of product or program management product marketing business development or technology experience
- Experience defining roadmap strategy and prioritizing deliverables for your team products
- Experience contributing to engineering discussions around technology decisions and strategy related to a product
- Experience with analytical tools and ability to dive deep into metrics and reporting
- Experience with manufacturing execution systems (MES) shop floor scheduling or production control software
- Experience managing technical products or online services in manufacturing or industrial environments

- Experience in high-volume manufacturing operations or sourcing environments
- Experience in practical work applying ML to solve complex problems
- Experience with concepts such as system architecture optimization system dynamics system analysis statistical analysis reliability analysis and decision making
- Experience in building and driving adoption of new tools
- Knowledge of cutting-edge production technologies and delivery workflows
- Masters degree in Computer Science Computer Engineering Systems Engineering Electrical Engineering or other related discipline
- Experience presenting complex ideas in writing in the form of authoring white papers proposals or other formal strategy documents
- Knowledge of IIoT protocols (OPC UA MTConnect MQTT) and industrial data integration
- Experience in high-volume high-mix manufacturing environments (metals fabrication welding coating assembly)
- Experience with ISO 9001 or similar manufacturing quality management systems
- Knowledge of Industry 4.0 principles smart manufacturing architectures or software-defined manufacturing

Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status disability or other legally protected status.

Our inclusive culture empowers Amazonians to deliver the best results for our customers. If you have a disability and need a workplace accommodation or adjustment during the application and hiring process including support for the interview or onboarding process please visit for more information. If the country/region youre applying in isnt listed please contact your Recruiting Partner.

The base salary range for this position is listed below. Your Amazon package will include sign-on payments and restricted stock units (RSUs). Final compensation will be determined based on factors including experience qualifications and location. Amazon also offers comprehensive benefits including health insurance (medical dental vision prescription Basic Life & AD&D insurance and option for Supplemental life plans EAP Mental Health Support Medical Advice Line Flexible Spending Accounts Adoption and Surrogacy Reimbursement coverage) 401(k) matching paid time off and parental leave. Learn more about our benefits at WA Bellevue - 151200.00 - 204600.00 USD annually