Amazon
System Development Engineer II, HWEngS Ultraservers
$129K–$201K
Austin, TX +2 · Full-time · Posted Oct 5, 2026
- Location
- Austin, TX
Seattle, WA
Cupertino, CA - Experience
- 2+ years in several specified areas; alternatives are not stated.
- Education
- Bachelor's degree in Computer Science, Computer Engineering, Electrical Engineering, or equivalent work experience.
About the job
Builds automation, diagnostics, and fleet-health systems to detect, diagnose, and prevent failures across GPU-accelerated servers.
What you'll do
- Develop fleet-health automation, predictive failure detection, diagnostics, monitoring, and test infrastructure.
- Debug system-level issues across hardware, firmware, Linux, drivers, networking, and accelerators; identify root causes and drive permanent fixes.
- Build scalable hardware test automation and telemetry pipelines, collaborating with engineering teams, operations, ODMs, and design partners.
What they ask for
- 2+ years of non-internship professional software development experience and 2+ years designing or architecting systems.
- 2+ years of administrative experience in networking, storage systems, operating systems, and hands-on systems engineering.
- Programming experience in at least one modern language, such as C++, C#, Java, Python, Golang, PowerShell, or Ruby; 2+ years of Linux experience.
- Experience leading design, build, and deployment of complex, performant production software solutions.
Nice to have
- Master's degree in computer science, electrical engineering, or related field.
- 2+ years of software development life cycle experience; Linux kernel driver development, OS internals, or GPU/accelerator driver integration and diagnostics experience.
Pay
148,700.00 - 201,200.00 USD annually (base salary); 129,200.00 - 174,800.00 USD annually (base salary); 129,200.00 - 174,800.00 USD annually (base salary)
Tools
C++, C#, Java, Python, Golang, PowerShell, Ruby, Linux
AI focus
Supports AI/ML accelerator infrastructure by building fleet-health automation and predictive diagnostics for GPU-accelerated servers.
Model-written summary · the original posting is authoritative