AWS Infrastructure Services owns the design, planning, delivery, and operation of all AWS global infrastructure. In other words, we're the people who keep the cloud running. We support all AWS data centers and all of the servers, networking, power, and cooling equipment that ensure our customers have continual access to the innovation they rely on. We work on the most challenging problems, with thousands of variables impacting the supply chain — and we're looking for talented people who want to help.

You'll join a diverse team of software, hardware, and network engineers, supply chain specialists, security experts, operations managers, and other vital roles. You'll collaborate with people across AWS to help us deliver the highest standards for safety and security while providing seemingly infinite capacity at the lowest possible cost for our customers. And you'll experience an inclusive culture that welcomes bold ideas and empowers you to own them to completion.

Our team designs, builds and operates Amazon's fleet of GPU-accelerated servers using Nvidia's latest GPU offerings to power AI/ML workloads across AWS's compute infrastructure. We solve systemic hardware issues and build hardware and software systems to detect and mitigate future recurrences so that our customers can experience the highest quality of service possible.

AWS Infrastructure Services is seeking a Senior Technical Program Manager to drive end-to-end delivery of GPU-accelerated servers powering AI/ML workloads across our global fleet. You will facilitate requirements gathering with internal customers, coordinate cross-functional engineering teams spanning hardware and software disciplines, manage ODM partnerships across multiple continents, and establish closed-loop quality feedback systems connecting operational data to design improvements.
This role requires technical depth to challenge engineering workstreams and translate technical constraints into program risk, combined with program management excellence to deliver complex hardware at global scale. You will maintain program schedules by identifying blockers early, escalate dependencies before they impact critical path, and ensure our AI/ML infrastructure meets reliability commitments through data-driven quality systems.

Key job responsibilities
Requirements & Planning: Facilitate requirements gathering sessions with internal customers and stakeholders. Work with engineering teams to validate feasibility, identify dependencies, and establish clear success criteria. Build program timelines with milestone tracking, critical path analysis, and proactive risk assessment. Translate business objectives into program deliverables that engineering teams can execute against.
Execution & Coordination: Drive cross-functional alignment across hardware, firmware, software, and operations teams to maintain development schedules. Manage ODM partnerships by tracking design reviews, manufacturing readiness gates, and quality checkpoints. Identify blockers early and escalate dependencies before they impact critical path. Facilitate decision-making when teams are stuck on technical trade-offs. Communicate program status to stakeholders with clear visibility into progress against milestones.
Risk & Issue Management: Identify program risks by challenging technical workstreams and connecting technical constraints to schedule impact. Escalate risks proactively with quantified business impact and proposed mitigation plans. Lead root cause analysis of fleet-wide hardware failures, driving engineering teams to implement corrective actions that improve operational metrics. Establish feedback loops connecting operational telemetry back to validation criteria for future designs.
Quality & Deployment: Define acceptance criteria and coordinate qualification testing across teams. Manage deployment readiness by tracking open issues, validating documentation completeness, and ensuring operations teams are prepared for production handoff. Facilitate go/no-go decisions with clear risk posture and mitigation status for mission-critical AI/ML workloads.
Transition & Closure: Conduct knowledge transfer sessions with receiving teams. Document lessons learned with actionable recommendations that improve future program execution. Ensure all program artifacts are complete and accessible.

A day in the life
Your day-to-day responsibilities will include interfacing with internal and external customers to understand project requirements and facilitate system development on GPU-accelerated server platforms. You will analyze operational challenges across the existing fleet with the goal of improving current customer experience and implementing design improvements for future generations.

You will work directly with ODM partners to coordinate development activities, manage vendor relationships, and drive manufacturing readiness at scale. As the end-to-end owner of complex server platforms, you will lead root cause analysis of fleet issues and implement closed-loop corrective actions that drive improvements back into development processes and design specifications.

About the team
The Ultra Server Hardware Engineering team is a group of engineers and technical program managers directly responsible for launching GPU-accelerated servers into the AWS fleet. Located in Seattle and Cupertino, we collaborate with global development teams and ODM partners to deliver next-generation AI/ML infrastructure deployed in datacenters worldwide.

Our team members bring diverse technical backgrounds but share a common commitment to Bias for Action and strong Ownership. We operate with a startup mentality, delivering fully functional solutions that power AWS's most demanding AI/ML workloads.