AI Infrastructure & Performance Engineer

Fortinet, Inc.; New York (NY); On-site; USD 215,000 - 350,000; Full time

Benefits offered by this job

Medical insurance

Dental insurance

Vision insurance

401(k)

Job summary

Fortinet, Inc. is seeking an AI Infrastructure Engineer to build and operate Linux and GPU-based infrastructure powering our AI platforms and performance testing environments. This hands-on role focuses on automation, reliability, and scalability to support customer demonstrations and technical evaluations.

You will design benchmarking systems, implement monitoring and incident response, and collaborate across labs to deploy and optimize compute resources for engineering and AI workloads.

Qualifications

• Hands-on Linux systems administration and infrastructure experience (servers, networking fundamentals, virtualization).
• Experience with KVM or containerization (Docker/Kubernetes).
• Familiarity with DevOps toolchains (CI/CD, IaC, monitoring/observability stacks).
• Strong scripting/automation ability in Python and/or Bash, applied to infrastructure or testing workflows.
• Practical experience with GPU-based compute environments or AI/ML infrastructure.

Responsibilities

• Operate, maintain, and enhance automated performance testing services that benchmark throughput, latency, scalability, and resource utilization.
• Develop new testing frameworks, automation, and validation methodologies as requirements evolve.
• Analyze performance data and recommend improvements to reliability, scalability, and operational efficiency.

Skills

Linux systems administration

Docker/Kubernetes

DevOps tooling (CI/CD, IaC, monitoring

Python/Bash scripting

GPU/AI infrastructure experience

Education

Bachelor's degree in Computer Science or related field

Tools

Docker

Kubernetes

CI/CD tools

Infrastructure as Code (IaC)

Monitoring/observability stacks

KVM virtualization

Job description

Fortinet, Inc. is seeking an AI Infrastructure Engineer to build and operate Linux and GPU-based infrastructure powering our AI platforms and performance testing environments. This hands-on role focuses on automation, reliability, and scalability to support customer demonstrations and technical evaluations.

You will design benchmarking systems, implement monitoring and incident response, and collaborate across labs to deploy and optimize compute resources for engineering and AI workloads.