Staff QA Engineer - Workload Management

Salary Range: PLN 350,700 - 474,400

Subject to alignment to the responsibilities and duties of the role.

Location: Gdańsk - Hybrid Working Policy - 2-3 Days per week in office

About Graphcore

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.

The Role

We are seeking a Quality Assurance Engineer to join our Workload Management team, which is responsible for enabling next-generation AI accelerator hardware within Kubernetes clusters.

In this role, you will contribute to the validation of Kubernetes integrations that allow new accelerator to be scheduled, orchestrated, and utilized efficiently across distributed environments.

Working closely with software engineers and infrastructure teams you will help ensure that our workload management stack - including scheduling, resource allocation, and device management - operates reliably in production environments. The role combines strong automation engineering with a systems-level understanding of distributed platforms, helping ensure our solutions are robust, scalable, and ready for real-world deployment.

As a senior member of the team, you will play an important role in mentoring engineers and shaping quality practices.

Responsibilities

• 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 within Kubernetes clusters.
• Identify, document, and track defects, working closely with engineering teams to investigate root causes and validate fixes.
• Contribute to design of CI/CD pipelines.
• Validate 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.
• Contribute to the evolution of QA automation frameworks, tooling, and testing practices across the organization.
• Mentor and support other QA engineers, providing guidance on automation, debugging, and testing best practices.

Skills and Experience

Essential

• Strong programming experience in Py