Senior Product Manger - Tech, Infrastructure Reliability
Amazon - Austin, Texas, USA
Posted Mar 30, 2026
Benefits
- Parental leave
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- Non-birth-parent leave
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- Family-building benefits
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- Fertility benefits: Not verified
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- Mental health support
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- Relocation assistance
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- Childcare support
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- Learning budget
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- Salary
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- 401(k) match
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Schedule
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- Weekend work
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Application
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- Deadline
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Where they hire
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About this role
Senior Product Manger - Tech, Infrastructure Reliability Austin, Texas, USA Join Amazon's Fulfillment Technologies & Robotics (FTR) team to spearhead the product vision for a platform that ensures Amazon's fulfillment network never stops - even as we move toward fully self-governing, zero-touch operations. You'll own the roadmap for an AI-powered infrastructure reliability platform that prevents, detects, and resolves incidents across thousands of fulfillment sites globally. This is a rare opportunity for a technically deep product leader who can write code, deliver proof-of-concepts, and engage as a peer with data scientists and engineers. You will shape how LLMs, multi-agent systems, and machine learning are applied to one of the most operationally critical platforms Amazon has ever built - and your hands-on technical contributions will directly accelerate the team's ability to move from idea to production. Key job responsibilities - Own and drive the multi-year product roadmap for the Infrastructure Reliability AI-Ops platform, spanning three strategic programs: zero-touch incident resolution, associate-directed work tooling, and predictive failure prevention. This means defining the vision, strategy, and success metrics for AI-powered progressive detection, incident consolidation, self-governing remediation orchestration, and cross-domain observability capabilities that serve thousands of fulfillment sites globally. - Go beyond traditional product management by writing code and delivering working proof-of-concepts that validate technical hypotheses before committing engineering resources. Whether prototyping a multi-agent reasoning pipeline, exploring a new anomaly detection approach, or stress-testing an LLM prompt chain against real incident data, you will use your technical skills to compress the distance between idea and
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