AI Infra Systems Engineer: GPU & Accelerator Servers

Amazon Web Services (AWS); Seattle (WA); On-site; USD 129,000 - 175,000; Full time

Benefits offered by this job

Health insurance

401(k) matching

Paid time off

Parental leave

Job summary

Amazon Development Center U.S., Inc. is seeking a Systems Development Engineer to own health and development of server platforms at worldwide fleet scale.

You will build automation, analyze telemetry across thousands of hosts, and create tooling that determines capacity availability for AI workloads. Responsibilities span hardware monitoring interfaces through fleet-wide data pipelines and dashboards, collaborating with software, hardware, and vendor teams to deliver scalable, reliable compute

Qualifications

• 2+ years of professional software development experience
• 1+ years of designing or architecting systems
• 3+ years of hands-on systems engineering experience in networking, storage, OS
• Knowledge of systems engineering fundamentals (networking, storage, OS)
• Experience with at least one modern language (C++, C#, Java, Python, Golang, PowerShell, Ruby)

Responsibilities

• Analyze fleet telemetry and logs to identify failure patterns and quantify customer impact
• Develop automation for hardware test, firmware qualification, and capacity recovery workflows
• Debug and resolve Linux boot/run issues across architectures (PCIe, Power, NIC, NVMe, GPU)
• Build scalable automation solutions using Python/Java or similar languages

Skills

Software development

System design

OS and kernel knowledge

Programming languages

Tools

PowerShell

Python

Ruby

Linux

Job description

Amazon Development Center U.S., Inc. is seeking a Systems Development Engineer to own health and development of server platforms at worldwide fleet scale.

You will build automation, analyze telemetry across thousands of hosts, and create tooling that determines capacity availability for AI workloads. Responsibilities span hardware monitoring interfaces through fleet-wide data pipelines and dashboards, collaborating with software, hardware, and vendor teams to deliver scalable, reliable compute