Hardware Systems Engineer - AI Hardware

Available Locations: Austin, Texas | Lisbon, Portugal

About The Department

Cloudflare’s Infrastructure group is responsible for building our global network. Our Hardware Engineering team helps research, develop, test, and deploy new equipment enabling 20% of the world’s internet traffic to be served smoothly. Deployed across 330 cities in 120+ countries, the hardware we select helps improve the security, reliability, and performance of the Internet.

About The Role

We need to make thoughtful infrastructure choices affecting a significant portion of the Internet. Hardware we work with includes GPUs, servers and components, as well as PDUs and network hardware. As a Hardware Systems Engineer, you will work with colleagues on the Engineering teams, Product and Performance teams, and Hardware Sourcing teams to design, qualify and maintain Cloudflare’s worldwide fleet of GPU servers.

What You'll Do

• Contribute to the technical requirements and end-to-end delivery of AI infrastructure — compute, networking, storage, power, and cooling — not just the accelerator
• Evaluate, select, and qualify AI hardware platforms (GPUs, custom ASICs, SmartNICs, storage) based on real workload requirements and first-principles analysis
• Design and validate rack-scale GPU systems: multi-node topologies, high-speed interconnects (NVLink, InfiniBand, RoCE), power distribution, and thermal management
• Run hands-on qualification: benchmarking, stress testing, failure mode analysis, and vendor RCA — you close the loop yourself
• Assess and qualify ODM/OEM server platforms; engage directly with vendors and work through the full technical qualification cycle
• Translate AI product and workload requirements into precise infrastructure specifications
• Identify gaps in the existing infrastructure stack and drive solutions across hardware, firmware, software, and operations
• Stay ahead of the AI hardware landscape — new silicon, new interconnects, new form factors — and bring informed, opinionated recommendations
• Build tooling and automation to support qualification workflows, performance analysis, and ongoing operational visibility
• Communicate your results and updates through blog posts and internal talks

Examples Of Desirable Skills, Knowledge And Experience

• Bachelor’s, Master’s, or PhD degree in Computer Engineering, Electrical Engineering, or Computer Science
• Experience in AI infrastructure, systems engineering, or hardware platform engineering
• First-principles understanding of AI accelerator architecture: compute pipelines, memory hierarchy (HBM, GDDR), interconnect topology, and/or how workload characteristics map to hardware capabilities
• Hands-on experience qualifying AI server platforms — you've run NCCL tests, profiled collective operations, debugged NVLink errors, and chased down PCIe lane misconfigurations
• Understand rack-scale systems: high-density power (kW/rack, busbar, PDU), liquid cooling (rear-door, direct liquid, immersion), high-speed networking infrastructure, and/or physical layer constraints
• Experience with AI/ML frameworks (vllm, sglang) at the systems level — you understand what they demand from the hardware and where bottlenecks actually live
• Familiarity with AI server form factors: HGX, OAC, OAM, UBB, open rack standards, and the tradeoffs between them
• Scripting and automation skills (Python, Bash, Go and Linux sysadmin); you build tooling to support your own work and the team's
• Strong written communication — you can write a rigorous technical specification and a crisp vendor requirements document
• Knowledge of performance benchmarking ; Previous experience in testing, measuring, and/or simulating hardware performance and an understanding of no-stone-left-unturned experimentation
• Knowledge of Redfish, IPMI and server remote management protocols, and experience with firmware updates
• Harness AI tools and automation to fundamentally accelerate the qualification lifecycle, driving exponential efficiency gains and quality standards.
• Possess the organizational skills and interest to manage cross-functional technical projects, ensuring architectural designs seamlessly align with delivery schedules.
• Thrive as a deeply self-motivated engineer in ambiguous environments, demonstrating a strong bias for action and the ability to drive initiatives forward without close supervision.

Bonus Points

• Experience with major AI server ODMs/OEMs and their qualification and customization processes
• Exposure to hyperscaler or cloud infrastructure design — understanding how GPU capacity is provisioned, allocated, and operated at scale
• Experience with RDMA networking, RoCEv2 congestion control, or InfiniBand fabric management
• Understanding of AI workload patterns: LLM training vs. inference, model/tensor/pipeline parallelism, and their memory and bandwidth implications
• Familiarity with open compute hardware programs or OCP specifications
• Experience of performance optimization based on hardware / software codesign
• Experience of kernel development, compiler optimization, or driver development.
• Experience of observability and monitoring tools such as Prometheus and Grafana, as well as the ability to observe trends over time
• Experience with software development tools and processes such as Git, TeamCity and Jira
• Experience in a hyperscale cloud infrastructure role also valuable
• Knowledge of debugging server hardware faults and the ability to engage with our sourcing team and vendors to improve quality

Who You Are

• A self-starter who identifies what needs to be done and executes without waiting to be asked
• Genuinely curious — you read architecture whitepapers, follow chip announcements, and have opinions on why one memory subsystem beats another
• Equally comfortable racking servers in a lab and writing a detailed technical requirements document
• Able to make a defensible technical decision with incomplete information, and communicate the reasoning clearly

Compensation

Compensation may be adjusted depending on work location.

• For Lisbon based hires: Estimated annual salary of €54,000-68,000

Equity

This role is eligible to participate in Cloudflare’s equity plan.

Benefits

Cloudflare offers a complete package of benefits and programs to support you and your family. Our benefits programs can help you pay health care expenses, support caregiving, build capital for the future and make life a little easier and fun! The below is a description of our benefits for employees in the United States, and benefits may vary for employees based outside the U.S.

Health & Welfare Benefits

• Medical/Rx Insurance
• Dental Insurance
• Vision Insurance
• Flexible Spending Accounts
• Commuter Spending Accounts
• Fertility & Family Forming Benefits
• On-demand mental health support and Employee Assistance Program
• Global Travel Medical Insurance

Financial Benefits

• Short and Long Term Disability Insurance
• Life & Accident Insurance
• 401(k) Retirement Savings Plan
• Employee Stock Participation Plan

Time Off

• Flexible paid time off covering vacation and sick leave
• Leave programs, including parental, pregnancy health, medical, and bereavement leave