Sr Systems Development Engineer, AWS Hardware Engineering Services, AI UltraServers

Fleet Health & Predictive Infrastructure

• Build and own the automation infrastructure for accelerator (AI/ML) fleet health at a large scale of servers, driving toward zero-touch operations that detect, diagnose, triage, and remediate faults without human intervention
• Design and develop test frameworks, test coverage strategies, and diagnostic tooling to validate hardware functionality, detect faults, and ensure qualification coverage across the platform lifecycle
• Design predictive failure detection using telemetry, sensor data, error trending, and log correlation to identify degrading components before customer impact
• Define and track fleet health metrics: failure rates, mean time to detect and resolve issues, first-time fix rate, test dwell time, and predictive accuracy
• Debugging & Troubleshooting
• Debug complex system-level issues across compute, GPU, and networking in production — including Linux boot/runtime failures, PCIe, power, NIC, NVMe, and GPU subsystems on x86 and ARM
• Perform root cause analysis correlating across firmware, kernel, driver, and physical layer; feed findings into manufacturing quality and design improvements

Systems Development & Automation

• Design scalable test automation for hardware bring-up, regression, and qualification — reducing manufacturing test cycle times without sacrificing coverage through intelligent test sequencing and parallel execution
• Build data pipelines correlating test results, sensor telemetry, and component-level data to identify systemic yield issues and drive upstream fixes
• Develop and maintain Linux device drivers on ARM and x86; work with OS internals and accelerator/GPU software stacks
• Build and manage tests covering all functional aspects of the system and CI/CD pipelines for rapid deployment to manufacturing lines and production fleet

Cross-Team Collaboration

• Engage with ODMs and design partners on testability, diagnostic coverage, and automation requirements during hardware design and bring-up phases — influencing functional and performance readiness of the platform
• Partner with datacenter operations to close the loop between field failures, manufacturing escapes, and design improvements

Operational Excellence

• Participate in post-incident reviews, identify contributing causes and drive permanent fixes that eliminate whole classes of risk
• Produce clear, maintainable documentation for systems, runbooks, and automation to enable others to operate and extend your work
• Drive process improvements that increase team agility — reducing development friction, eliminating unnecessary gates, and improving delivery velocity