AI Infrastructure Engineer
Fortinet
- Location
- Hybrid (New York, NY)
- Compensation
- $215k - $350k/yr
- Employment
- Full-time
- Level
- Senior Level
About the Role
Fortinet seeks an AI Infrastructure Engineer to build and maintain Linux and GPU-based infrastructure supporting AI platforms and performance testing. This role ensures reliability and scalability of compute environments to validate customer requirements and showcase AI solution capabilities.
Skills
Benefits
- Medical insurance
- Dental insurance
- Vision insurance
- Life insurance
- Disability insurance
- 401(k)
- Paid holidays
- Vacation time
- Sick time
- Leave program
Perks
- Equity program
- Commissions
- Hybrid Work
Full job details
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. You will design and maintain benchmarking frameworks, ensure the reliability and security of lab and compute environments, and develop internal AI platform services that support customer demonstrations, proof-of-concepts, competitive evaluations, and technical sales efforts. Your work will play a key role in helping secure new customer opportunities by enabling rapid validation of customer requirements and showcasing the performance and capabilities of our AI solutions.
Key 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.
Required Qualifications (Must-Have).
- 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.
Preferred 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
Fortinet offers employees a variety of benefits, including medical, dental, vision, life and disability insurance, 401(k), 11 paid holidays, vacation time, and sick time as well as a comprehensive leave program.
Wage ranges are based on various factors including the labor market, job type, and job level. 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.
All roles are eligible to participate in the Fortinet equity program, and this position is also eligible for commissions based on the terms of the Sales Compensation Plan
Fortinet makes possible a digital world that we can always trust through its mission to protect people, devices, and data everywhere. This is why the world’s largest enterprises, service providers, and government organizations choose Fortinet to securely accelerate their digital journey. The Fortinet Security Fabric platform delivers broad, integrated, and automated protections across the entire digital attack surface, securing critical devices, data, applications, and connections from the data center to the cloud to the home office. Ranking #1 in the most security appliances shipped worldwide, more than 615,000 customers trust Fortinet to protect their businesses. And the Fortinet NSE Training Institute, an initiative of Fortinet’s Training Advancement Agenda (TAA), provides one of the largest and broadest training programs in the industry to make cyber training and new career opportunities available to everyone.