Senior Data Center Connectivity Engineer

This role translates product reference architectures and logical network diagrams into physical builds, applying to NVIDIA's AI Factory build guidelines and large-scale internal research clusters. As the lead engineer for all in-cluster cabling, pathway and rack layout optimisations, you will ensure the cluster is co-designed with facilities infrastructure (Power & Cooling) and Infrastructure Software.

Key responsibilities include:

• Developing connectivity reference designs based on requirements from cluster architecture, network engineering, infrastructure software and product hardware teams.
• Building and developing comprehensive documentation, including detailed rack elevations and network architecture diagrams and cabling point-to-point list. Supporting projects throughout design and deployment phases.
• Serving as the primary engineering support, closely collaborating with deployment and field teams to ensure successful cluster build-out and operation.
• Strategically co-designing the cluster with power and cooling infrastructure teams, ensuring a thorough understanding of all facility architectural requirements (Arch, power, cooling).
• Working with hardware, network and security teams to translate software stack requirements into physical requirements: hardware selection, fault domain, network architecture.
• Developing new solutions and products in the connectivity space to accelerate the deployment of large-scale AI Factories.

Requirements include:

• A 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.
• A degree in a relevant field (BA or BS) or equivalent experience.
• A 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.

Benefits include eligibility for equity and benefits.