Principal Hardware Diagnostics Engineer

About the Position

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.

We are seeking an experienced Principal Hardware Diagnostics Engineer to design and develop diagnostics software used to monitor hardware health and diagnose system-level issues across Graphcore’s AI infrastructure platforms.

This role focuses on building diagnostics agents, tools, and analytics frameworks that enable engineers and automation systems to identify, isolate, and resolve hardware issues across blade-level servers and rack-scale clusters.

Responsibilities

• Design and develop automated hardware diagnostics solutions for blade-level servers and rack-scale AI systems.
• Architect and implement diagnostic agents, monitoring tools, and analytics frameworks to track hardware telemetry.
• Collaborate with hardware teams to integrate low-level diagnostic modules into monitoring systems.
• Develop diagnostics tools capable of detecting hardware health conditions and isolating failures.
• Create diagnostic modules used for internal validation and production data center operations.
• Provide detailed hardware fault information to system engineers to accelerate troubleshooting.
• Define remediation workflows and insights for hardware fault scenarios across nodes and clusters.
• Collaborate with firmware, networking, and cloud platform teams to integrate diagnostics across the system stack.

Requirements

Essential

• Bachelor’s, Master’s, or PhD in Computer Science, Computer Engineering, or related discipline.
• Strong software engineering experience in Python, C++, or C#.
• Experience developing diagnostics or monitoring systems for hardware platforms.
• Experience working with distributed systems or cloud infrastructure.
• Strong knowledge of Linux environments and system-level diagnostics tools.
• Experience collaborating with CM/ODM partners on manufacturing diagnostics and fault isolation.
• Strong analytical and debugging skills.
• Excellent communication and collaboration abilities.

Desirable

• Experience working with AI hardware platforms or accelerator-based computing systems.
• Familiarity with hyperscale data center infrastructure.
• Experience building cluster-level monitoring or diagnostics systems.
• Experience interacting with internal or external customers during diagnostics solution development.

We Offer

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 the Company

Graphcore is a globally recognized leader in Artificial Intelligence computing systems. The company designs advanced semiconductors and data center hardware that provide the specialized processing power needed to drive AI innovation, while delivering the efficiency required to support its broader adoption.

The Systems Engineering and Platform Validation team ensures Graphcore’s AI compute platforms are reliable, diagnosable, and operationally robust at scale. The team collaborates with hardware engineering, firmware, cloud infrastructure, and automation teams to develop tools and frameworks that monitor system health, detect hardware failures, and accelerate root-cause analysis across AI clusters.