资深云软件工程师

Salary Range: PLN 350,700- 474,400

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

Location: Gdańsk - Candidates must be local due to hybrid working policy

About the job

Make AI accelerator hardware feel native inside Kubernetes clusters.

As a Staff Cloud Software Engineer, you will build Go services that connect accelerator hardware with Kubernetes. You will own software components that turn complex compute capability into a usable platform experience.

Your work will shape how AI workloads discover, access and scale across cluster infrastructure. That means designing production services where reliability, performance and observability are part of the architecture.

You will build CRDs, operators and Kubernetes components for ML and platform teams. You will partner with hardware, cloud and ML engineers on design choices and roadmap priorities.

This is a senior IC role with room to set direction. You will mentor engineers, raise code quality and help define how Graphcore delivers cloud-native AI compute.

The team and culture

The Workload Management team sits between Kubernetes, cloud platforms and accelerator hardware. Work moves from architecture to implementation, review and production readiness without losing system context.

You will be trusted to own technical areas, challenge assumptions and move important work forward. The pace is driven by clear priorities, fast feedback and strong engineering judgement.

Decisions are made through evidence, prototypes and direct technical discussion. Engineers are expected to speak up early, share trade-offs and help the team learn quickly.

What we’re looking for

• Strong Go engineering experience, with significant experience delivering complex production software

• Deep Kubernetes architecture knowledge, including CRDs, operators and cloud-native

• Strong Go engineering experience, with significant experience delivering complex production software

• Deep Kubernetes architecture knowledge, including CRDs, operators and cloud-native integration patterns

• Solid Linux understanding, with the ability to debug issues across distributed systems

• Experience leading technical initiatives and mentoring engineers through design, review and delivery

• Ability to improve code quality, observability, automation and developer experience

• Clear C1-level English communication, with confidence working across hardware, cloud and ML teams

• Flexible working: Balance your work and personal life with greater flexibility

• Comprehensive healthcare and dental cover: Premium medical and dental insurance, with the option to extend cover to your family

• Phantom equity: Share in Graphcore’s success

• Fitness and wellbeing support: A fully funded Medicover gym card, giving you access to a wide range of gyms, fitness classes and leisure centres

• Financial protection: Death and disability insurance, providing financial security for you and your loved ones

• Retirement savings: Build your financial future, with a 4% employer contribution from Graphcore, alongside your own contributions

• Employee Assistance Programme (EAP): Confidential advice and support for you and your family across a range of personal, financial and wellbeing matters

We welcome people from all backgrounds and experiences and are committed to building an inclusive environment where everyone can do their best work.

We’re an equal opportunity employer and recognise that everyone brings different strengths and perspectives. If you need any adjustments during the interview process, just let us know - we’re happy to support you.

Sponsorship

Applicants must have the legal right to work in Poland. Unfortunately, we are unable to provide visa sponsorship or support visa applications for this role.

Join the Team at Graphcore

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 brings together deep expertise to solve complex problems and deliver meaningful progress in AI compute.

Ready to make Kubernetes the natural home for new AI accelerator hardware? Apply now to join Graphcore.

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

Location: Gdańsk - Candidates must be local due to hybrid working policy

About the job

Make AI accelerator hardware feel native inside Kubernetes clusters.

As a Staff Cloud Software Engineer, you will build Go services that connect accelerator hardware with Kubernetes. You will own software components that turn complex compute capability into a usable platform experience.

Your work will shape how AI workloads discover, access and scale across cluster infrastructure. That means designing production services where reliability, performance and observability are part of the architecture.

You will build CRDs, operators and Kubernetes components for ML and platform teams. You will partner with hardware, cloud and ML engineers on design choices and roadmap priorities.

This is a senior IC role with room to set direction. You will mentor engineers, raise code quality and help define how Graphcore delivers cloud-native AI compute.

The team and culture

The Workload Management team sits between Kubernetes, cloud platforms and accelerator hardware. Work moves from architecture to implementation, review and production readiness without losing system context.

You will be trusted to own technical areas, challenge assumptions and move important work forward. The pace is driven by clear priorities, fast feedback and strong engineering judgement.

Decisions are made through evidence, prototypes and direct technical discussion. Engineers are expected to speak up early, share trade-offs and help the team learn quickly.