Drimva

Amazon

Sr. System Development Engineer, Edge & High Performance Accelerator Servers for AI/ML

$151K–$235K

Austin, TX +2 · Senior · Full-time · Posted Jun 11, 2026

Location
Austin, TX
Seattle, WA
Cupertino, CA
Experience
6+ years in each of the three listed software development, systems/operations/automation, and systems design/architecture areas; 5+ years programming in at least one modern language.

About the job

Leads development of automation, diagnostic tools, and fleet-health systems for AWS edge and AI/ML accelerator servers, improving reliability through predictive detection and zero-touch remediation.

What you'll do

  • Build fleet-health infrastructure, predictive failure detection, monitoring, and automated fault diagnosis and remediation.
  • Debug system-level hardware and software issues across Linux servers, including compute, storage, networking, and GPU subsystems.
  • Lead server software and automation development and collaborate with hardware teams, ODMs, and operations through design, validation, launch, and fleet deployment.

What they ask for

  • 6+ years of non-internship professional software development experience.
  • 6+ years of systems design, software development, operations, automation, and process improvement experience; 6+ years designing or architecting new and existing systems.
  • 5+ years programming in at least one modern language, such as C++, C#, Java, Python, Golang, PowerShell, or Ruby.
  • Experience with Linux/Unix and leading the design, build, and deployment of complex, performant software solutions in production.

Nice to have

  • Experience building fleet-scale predictive failure detection or proactive remediation systems.
  • Experience with Linux kernel drivers, server hardware, GPU/accelerator platforms, or hardware development partners.

Pay

173,900.00 - 235,200.00 USD annually (base salary); 151,200.00 - 204,600.00 USD annually (base salary)

Tools

Linux, Unix, C++, C#, Java, Python, Golang, Ruby

AI focus

Develops and operates automation, predictive failure detection, diagnostics, and fleet-health systems for AI/ML accelerator servers and GPU platforms.

Model-written summary · the original posting is authoritative

First seen Oct 15, 2026 · Last verified Nov 4, 2026 (UTC)