AI Infrastructure Engineer

About the role

We are seeking an AI Infrastructure Engineer to build, operate, and continuously enhance the Linux and GPU-based infrastructure that powers our AI platforms and performance testing environments. This is a highly hands-on infrastructure, automation, and performance engineering role.

Responsibilities

• AI Infrastructure & Performance Engineering
  • 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.
• Server, Hardware & Platform Operations
  • Deploy, monitor, and optimize Linux servers, GPU clusters, virtualization platforms, and lab hardware.
  • Support availability and utilization of compute resources for engineering, testing, and AI workloads.
  • Evaluate and integrate new hardware technologies to improve performance and efficiency.
• Reliability Engineering & AI Platform Development
  • Implement monitoring, logging, alerting, failover, and incident response for critical infrastructure.
  • Develop, deploy, and maintain internal AI server applications and shared compute platforms.
  • Improve operational efficiency through automation and proactive issue identification; troubleshoot complex system/network/application issues.
• Laboratory Administration
  • Support day-to-day lab operations: access control, network administration, resource allocation, and capacity planning.
  • Contribute to operational standards and best practices for lab governance.
• Documentation & Knowledge Sharing
  • Create and maintain technical documentation: benchmarking reports, design notes, and internal runbooks.
  • Share technical insights and best practices with the broader engineering organization.

Requirements

• 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.

Qualifications

• Bachelor's degree in Computer Science, Computer Engineering, or a related field (equivalent experience welcome).
• Experience with performance testing, benchmarking, or traffic-generation methodologies.
• Exposure to network security concepts and enterprise security technologies.
• Experience with Fortinet products (FortiGate, FortiManager, FortiAnalyzer) or similar enterprise security/networking solutions — a plus, not required.
• Experience in customer-facing technical work: proof-of-concept support, demos, or technical presentations.
• Experience creating technical documentation, white papers, or delivering internal training.

Core Competencies

• Infrastructure Engineering
• AI Platform Development
• DevOps & Automation
• Performance Testing & Benchmarking
• Technical Documentation

Benefits

• Medical, dental, vision, life and disability insurance
• 401(k) with employer match
• 11 paid holidays, vacation time, and sick time
• Comprehensive leave program
• Eligibility for Fortinet equity program
• Commission eligibility based on Sales Compensation Plan

Pay

On target earnings for this position is expected to be $215,000 - $350,000 per year. Exact salary offers will be determined by factors such as the candidate's subject knowledge, skill level, qualifications, experience, and geographic location.