Why You Will Love It
The world's most advanced frontier models are trained on the platforms you help build. Your programs launch the GPU servers that power the largest AI/ML workloads on the planet. You will see your decisions reflected in fleet reliability metrics within weeks of deployment. The team is small and high-trust — you own programs end to end from concept through production, with direct access to leadership and engineering alike.
The Ideal Candidate
You have deep technical intuition across hardware and software — enough to challenge engineering decisions, not just track them. You thrive in ambiguity, bringing structure to programs where requirements, timelines, and dependencies are still forming. You align priorities across teams in different organizations, and you escalate with data, not noise. You actively mentor and develop others — TPMs and engineers alike. You contribute to hiring, promotion assessments, and raising the bar for program management practices in your organization.
Key job responsibilities
Strategy & Mechanisms
Define program strategy, objectives, and success criteria; influence resource allocation and priority decisions across engineering workstreams to align with organizational goals
Build and own mechanisms for program visibility — defining metrics, dashboards, and review cadences that enable data-driven decisions and early risk detection
Streamline delivery processes across teams; identify and eliminate dependencies, redundant gates, or coordination overhead that slow velocity
Requirements & Planning
Facilitate requirements gathering with internal customers; develop Technical Requirements Documents (TRDs) covering server specs, rack configurations, PCIe topology, power/cooling topology, and SKU definitions
Build program timelines aligned to different phases (Program Initiation, Design, Qualification, Pilot, Post-launch) with critical path analysis, risk identification with new & unique changes to the hardware, and milestone tracking for the program.
Drive Program Initiation reviews: scope definition, preliminary annualized failure rate predictions, resource planning, supply chain long-lead identification, and RFP (Request for Proposal) issuance to ODMs
Execution & Coordination
Drive cross-functional alignment across hardware, firmware (BIOS, BMC, CPLD), software, and operations teams through design reviews, manufacturing readiness and production readiness for fleet deployment.
Manage ODM partnerships: track EVT/DVT/PVT builds, manufacturing readiness gates, Bill of Materials (BOM) management in PLM systems, and quality checkpoints
Identify blockers early, escalate dependencies before they impact critical path, and facilitate technical trade-off decisions across engineering workstreams.
Communicate program status to leadership with clear reporting on milestone progress, risk posture, and mitigation plans.
Risk & Quality
Challenge technical workstreams to surface risks early; quantify impact to schedule and reliability (annualized failure rate targets, availability SLAs) with proposed mitigations
Drive root cause analysis of fleet-wide hardware failures and ensure corrective actions flow back into qualification criteria and design requirements
Define acceptance criteria, coordinate qualification testing at server and rack levels, and manage go/no-go decisions for mission-critical AI/ML workloads
Transition
Conduct knowledge transfer and document lessons learned; ensure operational readiness including automation, monitoring, and runbook completeness for production handoff
May require occasional (<10%) regional and international travel to Design and Manufacturing Partner sites.
A day in the life
You start the day syncing with ODM partners across time zones on build status and open engineering actions. Mid-morning, you run an engineering review connecting firmware, software, and hardware teams to unblock a qualification gate. In the afternoon, you triage a fleet reliability issue with operations data, drive alignment on corrective actions, and update executive stakeholders on program risk posture. You end the day reviewing NPI milestone readiness and ensuring the next design review has clear entry criteria.
About the team
The Hardware Engineering AI/ML UltraServer platform team is a group of engineers and technical program managers directly responsible for launching GPU-accelerated servers into the AWS fleet. Located in Seattle, Austin, and Cupertino, we collaborate with global development teams and ODM partners to deliver next-generation AI/ML infrastructure deployed in datacenters worldwide. We move fast with small, empowered teams delivering end-to-end — from server conception through fleet-scale operations.
Bachelor's degree in Computer Science, Computer Engineering, Electrical Engineering, or equivalent
6+ years of technical product or program management experience, working directly with multiple engineering teams.
6+ years of experience driving hardware development programs (servers, racks, networking, or storage) through full product lifecycle including design, validation, manufacturing, and fleet deployment
Experience managing programs across cross-functional teams, building processes, and coordinating release schedules
Master's degree in Computer Science, Electrical Engineering, or a related field
5+ years of experience coordinating complex server programs with ODM/JDM partners across multiple geographies, managing design reviews, manufacturing readiness gates, and quality checkpoints
5+ years of experience working with GPU/accelerator server platforms, NPI (New Product Introduction), or hardware qualification programs across various phases (EVT, DVT, PVT)
Experience driving root cause analysis and corrective action processes for hardware reliability issues at fleet scale
Knowledge of server hardware development lifecycle: electrical/mechanical design, firmware, thermal/power validation, and manufacturing testing.
Experience driving zero-touch automation or fleet health programs for large-scale infrastructure
Experience communicating engineering trade-offs and technical risks in business terms to leadership
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 https://amazon.jobs/content/en/how-we-hire/accommodations for more information. If the country/region you’re applying in isn’t listed, please contact your Recruiting Partner.
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