Principal Network Engineer
GraphcoreUS - MilpitasPosted 21 March 2026
Job Description
Graphcore is a globally recognized leader in Artificial Intelligence computing systems. The company designs advanced semiconductors and data centre hardware that provide the specialized processing power needed to drive AI innovation, while delivering the efficiency required to support its broader adoption.
As part of the SoftBank Group, Graphcore is a member of an elite family of companies responsible for some of the world’s most transformative technologies. We are opening a new AI Engineering Campus in Austin, which will play a central role in Graphcore's work building the future of AI computing.
RESPONSIBILITIES
Responsible for the maintaining all the network fabrics and network topologies operating at peak performance on Graphcore Data centers housing AI server platforms.
Collaborate closely with our Network architecture team through all phases of the design and development lifecycle — from concept to deployment — ensuring timely, high-quality, and stable high-speed network fabrics.
Primary support of deployed internal fabrics in our AI Datacenters.
Direct escalation for Hardware, Link and, Performance issues on network fabrics.
Escalation support for customer network fabrics (aligned to reference arch.)
Triage day-to-day network topologies (scale-up, scale-out, and front-end networks) issues of Fabrics deployed in Graphcore Datacenters.
REQUIREMENTS
Bachelor’s, master’s degree or equivalent experience in Network Engineering/Security, Information Technology, Computer Science, Computer engineering, or a related field.
9+ years of hands-on experience in network engineering and 3+ years supporting networking on AI or Hyperscale Datacenters.
Knowledge of Remote Direct Memory Access (RDMA) and its implementations, specifically ROCEv2 or InfiniBand
Knowledge of Lossless network – Experience with congestion control and lossless Ethernet technologies including PDF, ECN and DCQCN.
Versed in High-Bandwidth network infrastructure including experience with operating 400G and 800G network fabrics and tackling challenges at the physical layer for networks operating at these speeds. This includes familiarity with specific optical transceivers.
Experience sustaining non-blocking, multi-tier CLOS networks (i.e., Spine / Leaf / Super-Spine) that are optimized for high-density GPU clusters.
Extensive troubleshooting experience for data center routing protocols such as BGP and OSPF as well as troubleshooting of VXLAN implementations.
Cross-Functional collaboration- The candidate must excel at working closely with network architects, systems hardware engineers, AI software engineers, and Datacenter infrastructure teams to optimize the full stack from the application layer down to the Network infrastructure that includes controllers (NICs, SmartNICs, DPUs), network switches, and cabling and optical transceiver operation in our Datacenter.
DIFFERENTIATORS
Deep hands-on experience with NetDevOps to automate tasks using tools such as Terraform or Ansible to manage network configurations and state.
Possess strong scripting skills such as Python, Go, or JSON to build custom automation, interact with APIs, and develop internal network tools.
Deep hands-on experience with modern, high-performance hardware from network switch and NIC providers such as Broadcom, Arista, Cisco, or Pensando.
Knowledgeable in Advanced Network Telemetry, beyond traditional SNMP. Knowledgeable in telemetry protocols such as gNMI, Sflow, Netflow, Redfish, and Prometheus to characterize and detect transient congestion events, micro-bursts in the network fabric or defective network hardware.
We welcome people of different backgrounds and experiences and are committed to building an inclusive work environment that makes Graphcore a great home for everyone. We are an equal opportunity employer and want to build a work environment where everyone is happy, productive and respectful so they can do their best work. If you have a disability or additional need tha ... (truncated, view full listing at source)
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