The connectivity engineer translates product reference architectures and logical network diagrams into physical builds. This applies to NVIDIA's AI Factory build guidelines and NVIDIA's large-scale internal research clusters. This role will act as the lead engineer for all in-cluster cabling, pathway and rack layout optimizations required to power global-scale AI deployments, ensuring the cluster is co-designed with facilities infrastructure (Power&Cooling) and Infrastructure Software. This role provides an outstanding opportunity to be at the forefront of NVIDIA's technology roadmap!
What you'll be doing:
- Own the development of connectivity reference designs based on requirements from cluster architecture, network engineering, infrastructure software and product hardware teams.
- Build and develop comprehensive documentation, including detailed rack elevations and network architecture diagrams and cabling point-to-point list. Support projects throughout design and deployment phases.
- Serve as the primary engineering support, closely collaborating with deployment and field teams to ensure successful cluster build-out and operation.
- Strategically co-design the cluster with power and cooling infrastructure teams, ensuring a thorough understanding of all facility architectural requirements (Arch, power, cooling).
- Work with hardware, network and security teams to translate software stack requirements into physical requirements: hardware selection, fault domain, network architecture.
- Develop new solutions and products in the connectivity space to accelerate the deployment of large scale AI Factories
What we need to see:
- Minimum of 12+ years in a connectivity, network architecture or engineering role within a Hyperscale Cloud Provider, large-scale enterprise data center, or High-Performance Computing (HPC) environment.
- BA or BS (or equivalent experience).
- Consistent record of designing, deploying, and operating network fabrics for thousands of GPU/CPU nodes.
- Deep expertise in high-speed interconnect technologies, including InfiniBand, RoCE, and RDMA.
- Proven experience designing connectivity solutions for high-density GPU clusters (100kW+ per rack) and understanding the unique front-end and back-end requirements for AI training vs. inference.
- Deep understanding of data center infrastructure, including rack power/cooling, cable management, and physical density constraints.
- Demonstrated ability to lead multidisciplinary teams and complete sophisticated technical initiatives.
Ways to stand out from the crowd:
- Deep expertise with NVIDIA's compute and network product families and deployment standards.
- Comfortable operating at the intersection of network engineering, MEP systems, and Infrastructure as a Service software layer.
- Experienced with field deployments and/or global reference design documentation, ideally both.
Your base salary will be determined based on your location, experience, and the pay of employees in similar positions. The base salary range is 208,000 USD - 333,500 USD.
You will also be eligible for equity and benefits.
Applications for this job will be accepted at least until May 30, 2026.
This posting is for an existing vacancy.
NVIDIA uses AI tools in its recruiting processes.
NVIDIA is committed to fostering a diverse work environment and proud to be an equal opportunity employer. As we highly value diversity in our current and future employees, we do not discriminate (including in our hiring and promotion practices) on the basis of race, religion, color, national origin, gender, gender expression, sexual orientation, age, marital status, veteran status, disability status or any other characteristic protected by law.