AI Infrastructure Engineer

Fortinet

Confirmed live today High trust
Hybrid

Quick summary

Work type
Hybrid
Location
New York, NY
Salary
$215,000–$350,000 / yr
Employment
Full-time
Posted
60 days ago
Freshness
Confirmed live today

Market check

Salary context

Above market

How this pay compares to similar roles

Similar $183k
This role $282k
$98k $377k
below market most similar roles pay here above market

This role pays more than 96% of similar roles. Most pay $144,350–$221,100 — the blue band above. At the midpoint, this role pays about $282k versus about $183k for comparable roles.

Based on 240 similar postings.

Employer

About Fortinet

Fortinet is a US-based cybersecurity company best known for its FortiGate next-generation firewalls. It sells a broad security platform spanning network security, SD-WAN, endpoint protection, cloud security, and SIEM/SOC operations.

Fortinet currently has 102 open roles on FindRole.

Listed pay typically runs $140,000–$183,000 across 77 roles with salary data.

Most-posted roles

View all roles at Fortinet

At a glance

TL;DR · AI Infrastructure Engineer

The AI Infrastructure Engineer will join the team to build, operate, and enhance the Linux and GPU-based infrastructure powering AI platforms and performance testing environments. This hands-on role involves designing benchmarking frameworks, maintaining lab and compute environments, and developing internal AI platform services to support customer demonstrations and proof-of-concepts. Key responsibilities include operating automated performance testing services to benchmark throughput and latency, deploying Linux servers and GPU clusters, and implementing monitoring, logging, and failover systems. The candidate must possess skills in Linux systems administration, networking fundamentals, virtualization, and containerization using Docker or Kubernetes. Required technical proficiencies include Python and Bash scripting for automation, DevOps toolchains like CI/CD and IaC, and experience with GPU-based compute environments to solve complex infrastructure and performance engineering problems.

What you'll do

  • Operate and enhance automated performance testing services to benchmark throughput, latency, and scalability.
  • Develop new testing frameworks and validation methodologies as technical requirements evolve.
  • Deploy, monitor, and optimize Linux servers, GPU clusters, and virtualization platforms.
  • Implement monitoring, logging, alerting, and incident response for critical AI infrastructure.
  • Develop and maintain internal AI server applications and shared compute platforms.
  • Manage day-to-day lab operations including network administration, resource allocation, and capacity planning.
  • Create technical documentation such as benchmarking reports, design notes, and internal runbooks.

What we're looking for

  • Hands-on Linux systems administration and infrastructure experience including servers, networking fundamentals, and virtualization.
  • Experience with KVM or containerization technologies like Docker and Kubernetes.
  • Familiarity with DevOps toolchains including CI/CD, Infrastructure as Code, and monitoring/observability stacks.
  • Strong scripting and automation ability in Python and/or Bash for infrastructure or testing workflows.
  • Practical experience with GPU-based compute environments or AI/ML infrastructure.
  • Bachelor's degree in Computer Science, Computer Engineering, or a related field (preferred).
  • Experience with performance testing, benchmarking, or traffic-generation methodologies (preferred).
  • Experience in customer-facing technical work such as proof-of-concept support or technical presentations (preferred).

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