--- title: 'Senior Principal Network Engineer at Graphcore' canonical: 'https://feeny.ai/job/senior-principal-network-engineer-graphcore-austin-texas-mhxaw32kxv91' type: 'job' last_seen: '2026-09-08' --- # Senior Principal Network Engineer at Graphcore - **Company:** Graphcore - **Location:** Austin Texas, United States - **Posted:** 2026-03-16 - **Last confirmed live:** 2026-09-08 - **Apply:** https://job-boards.greenhouse.io/graphcore/jobs/8463815002 ## Job description ## About us Graphcore is one of the world’s leading innovators in Artificial Intelligence compute. It is developing hardware, software and systems infrastructure that will unlock the next generation of AI breakthroughs and power the widespread adoption of AI solutions across every industry. 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. Together, they share a bold vision: to enable Artificial Super Intelligence and ensure its benefits are accessible to everyone. Graphcore’s teams are drawn from diverse backgrounds and bring a broad range of skills and perspectives. A melting pot of AI research specialists, silicon designers, software engineers and systems architects, Graphcore enjoys a culture of continuous learning and constant innovation. Job Summary We are seeking a Senior Principal Network Engineer to help design, deploy, and optimize next‑generation AI data center networks. AI training and inference workloads require extremely high bandwidth, deterministic low latency, and zero‑packet‑loss networking environments. In this role, you will partner closely with the Network Architecture Lead to design and scale high‑performance computing (HPC) network fabrics supporting GPU clusters. You will work across hardware, networking, and AI application layers to ensure Graphcore’s large‑scale AI infrastructure operates at peak performance. The ideal candidate brings deep experience operating hyperscale or HPC data center networks and has expertise in high‑speed Ethernet fabrics, RDMA technologies, advanced automation, and telemetry systems. The Team The Data Center Network Engineering team designs and operates the high‑performance network fabrics that power Graphcore’s AI compute platforms. The team collaborates closely with hardware engineering, AI researchers, and infrastructure teams to build scalable networking environments optimized for distributed training and inference workloads. Engineers work on pioneering technologies including high‑speed Ethernet fabrics, lossless networking, RDMA transport, and large‑scale automation frameworks to support next‑generation AI clusters. ## Responsibilities and Duties - Assist in defining ultra‑high‑bandwidth, non‑blocking AI network fabrics (Clos spine‑leaf‑super‑spine architectures) for large‑scale distributed AI workloads. - Optimize performance of lossless Ethernet fabrics using congestion control mechanisms such as PFC, ECN, and DCQCN to support RDMA/RoCEv2 communication. - Lead initiatives to implement NetDevOps practices and develop automation for provisioning, configuration management, and network remediation. - Design and deploy high‑resolution telemetry pipelines to monitor network health, detect microbursts, and analyze congestion patterns. - Support modeling, deployment, configuration, and monitoring of data center network fabrics including scale‑out, scale‑up, and front‑end networks. - Collaborate cross‑functionally with hardware engineers, AI researchers, and data center operations teams to co‑design high‑performance infrastructure. - Provide technical leadership and mentorship to network engineers while establishing best practices and operational standards. - Contribute to the long‑term networking strategy and roadmap for Graphcore’s AI infrastructure. - Research and evaluate next‑generation high‑speed networking technologies and vendor solutions. Candidate Profile Essential - BS or MS or equivalent experience in Computer Science, Electrical Engineering, Network Engineering, or related technical discipline. - 12+ years of progressive network engineering experience with at least 3 years in hyperscale, high‑density, or HPC data center environments. - Expert‑level knowledge of data center routing and switching protocols including BGP, OSPF, and EVPN‑VXLAN architectures. - Strong operational understanding of RDMA networking technologies such as RoCEv2 or InfiniBand. - Hands‑on experience with modern merchant silicon networking platforms and NOS platforms such as Arista EOS, Cisco NX‑OS, or SONiC. - Experience deploying high‑speed network technologies including 400G/800G optics and large‑scale fabric architectures. - Proficiency in automation and scripting languages such as Python, Go, Bash, or similar tools. - Strong collaboration and communication skills across cross‑functional engineering teams. Desirable - Experience operating large‑scale AI or GPU clusters. - Familiarity with network telemetry frameworks and streaming analytics. - Experience implementing NetDevOps workflows and infrastructure automation pipelines. - Experience influencing vendor roadmaps or evaluating next‑generation networking technologies. In addition to a competitive salary, Graphcore offers flexible working and a comprehensive benefits package designed to support your health, wellbeing and financial future. Our benefits include medical, dental and vision coverage, Flexible Spending Accounts (FSAs), Health Savings Accounts (HSAs), disability and life insurance, a 401(k) retirement plan, commuter benefits, wellness services and an Employee Assistance Programme (EAP). We welcome people of different backgrounds and experiences; we're committed to building an inclusive work environment that makes Graphcore a great home for everyone. We offer an equal opportunity process and understand that there are visible and invisible differences in all of us. We can provide a flexible approach to interview and encourage you to chat to us if you require any reasonable adjustments. ## About Graphcore ## Company Overview - **One-liner**: Graphcore designs and builds the Intelligence Processing Unit (IPU), a processor purpose-built for machine intelligence, and provides a complete AI compute stack from silicon to software. - **Entity Type**: Private (wholly owned subsidiary of SoftBank Group Corp as of 2025/2026) - **Headquarters**: Bristol, England, UK - **Founded**: 2016 - **Founders**: Nigel Toon and Simon Knowles ## Core Business - **Primary industry**: AI hardware/accelerators, semiconductor design, AI software platform - **Target customers**: Cloud providers (Microsoft Azure), enterprises, AI researchers, hyperscalers - **Mission statement**: “Let innovators create the next breakthroughs in machine intelligence to enhance human potential” ## Products & Services - **[IPU (Intelligence Processing Unit)](https://www.graphcore.ai/)**: A processor designed from the ground up for machine intelligence workloads; uses a massively parallel architecture (MIMD) with fine-grained compute and on-chip memory. - **[IPU-Machine M2000](https://www.graphcore.ai/about)**: Second-generation IPU platform – a 1U server appliance housing 4 MK2 GC200 IPU processors, delivering an 8× performance uplift over the first generation. - **[C2 IPU Accelerator PCIe Card](https://www.graphcore.ai/about)**: PCIe form factor accelerator for server integration, first demonstrated at ICML 2018. - **[Poplar Software Stack](https://www.graphcore.ai/)**: Full SDK and framework integration (PyTorch, TensorFlow) that lets developers target the IPU directly. ## Market Standing - **Valuation/Market Cap**: Acquired by SoftBank Group Corp (amount undisclosed); prior to acquisition valued at $2.77 B (Series E, lead by Ontario Teachers’ Pension Plan Board). - **Key Metric**: Total funding raised prior to acquisition – over $680 M across Series A through E. - **Notable Investors/Partners**: SoftBank (owner), Microsoft (customer and investor), BMW, Samsung, Dell Technologies, Bosch, Sequoia Capital, Atomico, Fidelity, Baillie Gifford, Ontario Teachers’. - **Growth Signals**: Part of the fast-growing SoftBank AI ecosystem; expanding teams globally (Bristol, London, Cambridge, Gdańsk, Hsinchu, Bengaluru); first customer (Microsoft Azure) live since 2018. ## Competitive Advantages - **First purpose-built AI processor**: The IPU architecture is fundamentally different from GPUs – designed specifically for the sparse, parallel nature of neural network computation. - **Full stack ownership**: Graphcore controls silicon, system hardware, and software (Poplar), enabling tight optimisation across the entire compute chain. - **Cloud + on‑prem availability**: IPUs are available in the cloud on Microsoft Azure and as hardware from Dell, giving customers flexible deployment options. - **Strong IP and ecosystem**: 99+ engineering staff; deep expertise in semiconductor, systems, and AI software, backed by long-term SoftBank investment. ## Strategic Focus - **Scale AI infrastructure**: Delivering key technology into SoftBank’s global AI ecosystem and expanding the IPU platform to meet growing demand for AI compute. - **Expand into new regions**: Opening offices and hiring in India (Bengaluru) and across Europe (Gdańsk, London, Cambridge) to accelerate R&D and customer support. - **Democratise AI**: Continuing to lower the barrier for machine intelligence by providing accessible, high-efficiency hardware and software for innovators worldwide. ## Why Work Here - **Flexible hybrid work**: Employees are expected on-site three days a week, with trust and flexibility to balance work and life. - **Comprehensive benefits**: Unlimited annual leave, private medical insurance (UK), dental & health cash plan, income protection, life assurance, pension matched up to 5%, generous parental leave, and a personal development plan. - **Culture and growth**: ML reading groups, board game socials, book clubs, yoga, running, watersports, team events; strong DE+I initiatives; ambitious but supportive environment. - **Perks**: Free barista‑made coffee, snacks, and wellbeing rooms; cycle‑to‑work scheme; gym membership discount; education/training allowances. - **Purpose-driven work**: Opportunity to shape the future of AI compute and see your contributions used by global innovators. ## Sources 1. [graphcore.ai/about](https://www.graphcore.ai/about) 2. [graphcore.ai/](https://www.graphcore.ai/) 3. [graphcore.ai/careers](https://www.graphcore.ai/careers) 4. [graphcore.ai/jobs](https://www.graphcore.ai/jobs) 5. [builtin.com/company/graphcore](https://builtin.com/company/graphcore) ## Other roles at Graphcore - [Technical Programme Manager](https://feeny.ai/job/technical-programme-manager-graphcore-bristol-tnv81pjcg71q) — Bristol, United Kingdom - [Technology Owner](https://feeny.ai/job/technology-owner-graphcore-bristol-d8detpv2a2gt) — Bristol, United Kingdom - [Staff Silicon Physical Design Engineer - Bengaluru](https://feeny.ai/job/staff-silicon-physical-design-engineer-bengaluru-graphcore-bengaluru-5zwkhyr3ps27) — Bengaluru, India - [Staff Robotics Engineer](https://feeny.ai/job/staff-robotics-engineer-graphcore-austin-texas-48zjd6k5bqkd) — Austin Texas, United States - [Staff Engineering Program Support](https://feeny.ai/job/staff-engineering-program-support-graphcore-milpitas-california-hrx7htcx8rkq) — Milpitas California, United States - [Senior Engineering Program Coordinator](https://feeny.ai/job/senior-engineering-program-coordinator-graphcore-milpitas-california-k5rv0zfbxp3p) — Milpitas California, United States - [Staff Engineering Operations Technical Program Manager](https://feeny.ai/job/staff-engineering-operations-technical-program-manager-graphcore-austin-texas-ffy430feqmnr) — Austin Texas, United States - [Principal Network Program Manager, AI Infrastructure](https://feeny.ai/job/principal-network-program-manager-ai-infrastructure-graphcore-milpitas-ta509snr3rw9) — Milpitas California, United States - [Principal Engineering Program Manager](https://feeny.ai/job/principal-engineering-program-manager-graphcore-austin-texas-m5g623168tsj) — Austin Texas, United States - [Staff Hardware Engineer](https://feeny.ai/job/staff-hardware-engineer-graphcore-austin-texas-tf5ew0k0z9g8) — Austin Texas, United States