AI Infrastructure Engineer

What you'll do

• Operate and improve automated performance testing, benchmarking frameworks, and validation methods.
• Deploy, monitor, and optimize Linux servers, GPU clusters, virtualization platforms, and lab hardware; implement infrastructure reliability and incident-response capabilities.
• Develop and maintain internal AI server applications and shared compute platforms, and document operational practices.

What they ask for

• Hands-on Linux systems administration and infrastructure experience, including servers, networking fundamentals, and virtualization.
• Experience with KVM or containerization such as Docker/Kubernetes.
• Familiarity with DevOps toolchains, including CI/CD, IaC, and monitoring/observability stacks.
• Strong Python and/or Bash scripting and automation ability, plus practical experience with GPU-based compute environments or AI/ML infrastructure.

Nice to have

• Performance testing, benchmarking, or traffic-generation experience; exposure to network security concepts and enterprise security technologies.
• Fortinet products or similar solutions; customer-facing technical work, technical documentation, white papers, or internal training experience.

Pay

$215,000 - $350,000 per year (on target earnings; compensation type not specified)

Tools

Linux, KVM, Docker, Kubernetes, CI/CD, IaC, Python, Bash

AI focus

Develop and maintain internal AI server applications and shared compute platforms, and operate GPU-based infrastructure for AI workloads and performance testing.