Quality Assurance Engineer - Workload Management

At Graphcore, we’re building the future of AI compute. We’re a team of semiconductor, software and AI experts, with deep experience in creating the complete AI compute stack - from silicon and software to infrastructure at datacenter scale. As part of the SoftBank Group, backed by significant long-term investment, we are delivering key technology into the fast-growing SoftBank AI ecosystem. To meet the vast and exciting AI opportunity, Graphcore is expanding its teams around the world. We are bringing together the brightest minds to solve the toughest problems, in a place where everyone has the opportunity to make an impact on the company, our products and the future of artificial intelligence.

Essential:

• Programming experience in Python.
• Hands-on experience with Robot Framework or similar automation frameworks.
• Good understanding of Linux systems.
• Experience with CI/CD systems such as GitLab CI or GitHub Actions.
• Experience testing distributed systems.
• Ability to debug complex issues across multiple system layers (Kubernetes, infrastructure, applications).
• Good analytical and problem-solving skills.

Desirable:

• Experience validating Kubernetes integrations.
• Understanding of AI training and inference workloads and their orchestration requirements.
• Experience testing cloud-native systems and containerised environments.

• Design, develop, and maintain automated test suites for Kubernetes integration components.
• Develop end-to-end, integration, and system tests to validate scheduling and resource allocation across Kubernetes clusters.
• Identify, document, and track defects while working closely with engineering teams to investigate root causes and verify fixes.
• Contribute to design of CI/CD pipelines.
• Validate the scalability, performance, and reliability of workload orchestration.
• Improve test coverage, test stability, and observability across distributed system components.
• Collaborate with development teams to define quality standards, test strategies, and validation plans early in the development lifecycle.