---
title: 'Principal Engineer at Graphcore'
canonical: 'https://feeny.ai/job/principal-engineer-graphcore-austin-texas-yr942w2hq461'
type: 'job'
last_seen: '2026-09-08'
---

# Principal Engineer at Graphcore

- **Company:** Graphcore
- **Location:** Austin Texas, United States / Milpitas California, United States
- **Posted:** 2026-08-11
- **Last confirmed live:** 2026-09-08
- **Apply:** https://job-boards.greenhouse.io/graphcore/jobs/8694587002

## 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, spanning AI research specialists, silicon designers, software engineers and systems architects.

Job Summary

We are looking for an experienced Principal Engineer to join our System Management team and help lead the development of critical interfaces used by internal and external customers to manage system state. You will provide technical leadership within assigned areas of System Management, guide architecture and implementation choices, mentor engineers and translate broader technical direction into effective execution. This is a hands-on engineering role for someone who can lead complex technical work, improve reliability and operational readiness, and collaborate effectively across multiple engineering disciplines.

The Team

The System Management team sits within the Software Platform group and helps build Graphcore products into large-scale AI solutions for our customers.

The team is responsible for developing the interfaces between hardware, AI software and frameworks, as well as providing interfaces for public and private cloud environments. This includes system management capabilities that abstract complex hardware administration and enable reliable deployment and operation at scale.

As one of the first teams to work with new hardware and software, we regularly solve complex system-level problems in environments where components and interfaces are still evolving. The role requires strong technical judgement, adaptability and an ability to work effectively across engineering teams.

## Responsibilities and Duties

- Convert agreed System Management direction into technical plans, engineering priorities and deliverable work for assigned areas.
- Provide technical leadership for architecture and design decisions, building alignment across collaborating teams and documenting important technical trade-offs.
- Act as a technical authority for assigned areas of System Management, leading the delivery of large and complex engineering initiatives and coordinating technical plans, dependencies, risks and decisions.
- Provide technical direction and mentoring to engineers working across system management, hardware lifecycle management, deployment automation and production operations.
- Take responsibility for key technical outcomes across the full software lifecycle, including design, implementation, automated testing, integration, deployment, observability and production readiness.
- Identify systemic reliability, scalability and operability issues and lead practical improvements across the platform.
- Collaborate with Hardware, Firmware, Platform Software and Datacenter Operations teams to diagnose system-level issues and improve end-to-end product behaviour.
- Improve engineering standards and working practices, including CI/CD, Infrastructure-as-Code, automated testing, release safety and learning from operational incidents.
- Act as a senior technical escalation point for complex issues while creating reusable knowledge, tooling and automation that reduce future operational effort.

Candidate Profile

Essential

- Bachelor’s degree or equivalent practical experience in a relevant subject.
- Substantial experience designing, building and operating Linux-based infrastructure or distributed systems.
- Demonstrated experience providing technical leadership for complex engineering initiatives involving multiple teams or stakeholder groups.
- Experience influencing architecture and technical decisions across team boundaries without relying on formal authority.
- Experience translating broad technical goals into scoped plans, milestones, technical decisions, risks and delivery priorities.
- Strong experience developing RESTful APIs and programming in Go, with Bash and Python used for systems automation.
- Deep practical experience with Kubernetes, container runtimes and operating production workloads.
- Hands-on experience with Infrastructure-as-Code, source control and CI/CD technologies such as Terraform/OpenTofu, Ansible, GitLab, GitHub Actions and Git.
- Experience with hardware-management interfaces such as Redfish, IPMI or equivalent management systems.
- Strong Linux systems engineering, troubleshooting and operational debugging capability.
- Demonstrated ability to develop other engineers through technical mentoring, design reviews and coaching.
- Clear communication skills, with the ability to persuade, build alignment and bring stakeholders together around practical technical outcomes.

Desirable

- Experience using AI coding assistants effectively within professional engineering workflows.
- Experience developing Kubernetes operators and custom resources.
- Experience with High Performance Computing environments using SLURM, LSF or similar workload-management systems.
- Experience with virtualisation technologies such as Open vSwitch, KVM and QEMU.
- Experience with distributed object, block and file storage technologies such as Ceph.
- Experience with monitoring and observability platforms such as Grafana, Prometheus, OpenSearch/Elasticsearch, Loki, Mimir or OpenTelemetry.
- Experience configuring managed network switches using technologies such as EOS, SONiC or DNOS.
- Experience supporting AI infrastructure or PyTorch workloads.

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)

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