About the role
What will you do at Fortinet?
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.
Which skills does this role require?
Make your next move
Build a shortlist and prepare
Identify the requirements you can demonstrate, then choose examples from your work to discuss with the hiring team.
- Build a focused shortlist before you applyCompare role requirements with your experience and give each application a clear reason.
- Platform engineering jobsCompare current openings and review what to look for in this role.
- Practice explaining your experience in an interviewRehearse your answers before meeting the hiring team.
Other roles to compare
Review the responsibilities and requirements before adding an opening to your shortlist.
Machine Learning Infrastructure Engineer
Bright Vision Technologies · Hillsboro, Oregon, United States
Senior Machine Learning Engineer - ML Training Infrastructure
General Motors · Sunnyvale, California, United States
Senior AI Infrastructure Software Engineer - DGX Cloud
NVIDIA · Redmond, Washington, United States
Senior Infrastructure Engineer - Data Protection
USAA · Tampa, Florida, United States
AI Infrastructure AI/ML Engineer (100 % remote) (m/f/d)
EWOR · Capon Bridge, West Virginia, United States
Security Engineer - Infrastructure Security
Figure · San Jose, California, United States
Role information can change. Confirm current details on the original application page.
