AI Platform Systems Support Engineer (Austin)

Experis Austria; Austin (TX); On-site; USD 55,000 - 58,000; Full time

Benefits offered by this job

Medical Plans

Dental Plan

Vision Plan

401(k) Plan with match

Weekly Pay

Job summary

Our client, a leading technology organization, seeks a Systems Support Specialist in Austin, TX to provide technical support for AMD Ryzen AI Halo platforms across Windows and Linux.

You will analyze issues, collaborate with engineering teams, and assist customers with platform configuration, performance tuning, and best practices for AI workloads. Expect proactive problem solving and detailed reporting to drive improvements.

Qualifications

• At least 3 years of experience in technical support, system validation, or software support roles.
• Strong knowledge of Windows, Linux, and x86 platform architecture.
• Proficiency in scripting languages such as Python, Bash, or PowerShell.
• Excellent troubleshooting skills and ability to communicate effectively with customers and team members.
• Experience supporting AMD platforms, ROCm, GPU/NPU compute, or AI/ML frameworks is a plus.

Responsibilities

• Provide technical support and issue resolution for AMD Ryzen AI Halo platforms across Windows and Linux operating systems.
• Analyze and troubleshoot hardware, firmware, drivers, and software issues to ensure optimal platform performance.
• Collaborate with engineering teams to diagnose root causes and develop effective fixes or patches.
• Assist customers with platform configuration, performance tuning, and best practices for AI workloads.
• Generate reports and documentation to track issue trends and support continuous improvement efforts.

Tools

Python

Bash

PowerShell

Job description

Our client, a leading technology organization, seeks a Systems Support Specialist in Austin, TX to provide technical support for AMD Ryzen AI Halo platforms across Windows and Linux.

You will analyze issues, collaborate with engineering teams, and assist customers with platform configuration, performance tuning, and best practices for AI workloads. Expect proactive problem solving and detailed reporting to drive improvements.