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Automation Engineer

Job in Georgetown, Williamson County, Texas, 78628, USA
Listing for: Pegatron Technologies LLC
Full Time position
Listed on 2026-06-19
Job specializations:
  • Engineering
    Hardware Engineer
Salary/Wage Range or Industry Benchmark: 70000 - 90000 USD Yearly USD 70000.00 90000.00 YEAR
Job Description & How to Apply Below

Position Summary

This Automation Engineer role is ideal for building and maintaining the infrastructure, testing frameworks, and diagnostic tools for our next‑generation AI server platforms. This position is located in Austin, TX, with an

Role Overview

As an Associate AI Server Automation Engineer, you will work closely with hardware and software teams to develop automation scripts, diagnostic tools, and monitoring software for AI training clusters. You will test, deploy, and support the hardware infrastructure that scales generative AI.

Key Responsibilities
  • Infrastructure Automation: Develop and maintain Infrastructure‑as‑Code (IaC) and configuration scripts to deploy and manage AI server clusters.
  • Test & Diagnostics: Build and execute automated test suites (Python, Bash) to validate hardware stability, power draw, thermal limits, and interconnect performance.
  • Fleet Health Tracking: Create telemetry and monitoring dashboards for large‑scale GPU/AI servers to catch and debug hardware or firmware anomalies.
  • Server Architecture Support: Assist in troubleshooting, benchmarking, and optimizing enterprise AI servers (with a focus on modern high‑density architectures). [1]
  • CI/CD Pipeline Maintenance: Maintain and optimize continuous integration pipelines for firmware and hardware‑level tests.
Qualifications
  • Experience: 0–3 years of hands‑on experience in server automation, hardware validation, or systems engineering.
  • Programming: Strong scripting and programming skills in Python, C++, or Bash.
  • Technical Knowledge: Foundational understanding of Linux/Unix environments, network protocols, and enterprise hardware (GPUs, CPUs, and accelerators).
  • Education: Bachelor’s Degree in Computer Science, Computer Engineering, Electrical Engineering, or equivalent experience.
  • Soft Skills: Strong analytical problem‑solving skills, ability to collaborate with cross‑functional teams, and a desire to learn about the AI hardware ecosystem.
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