Keen to join a company that champions growth and development? Join one of the most exciting AI infrastructure companies in the market, building a platform that deploys and operates large-scale GPU clusters for some of the world's leading AI labs. Working with tens of thousands of GPUs across a global network of data centres, the organisation delivers the infrastructure powering next-generation AI training and inference at scale. This role offers the opportunity to work on complex, production-scale AI infrastructure without the layers of bureaucracy often found in larger organisations. You'll have the freedom to shape how the platform evolves while solving engineering challenges that have a direct impact on customers. Ready to make a move? Get in touch and apply today! Responsibilities: • You will be building and operating the automated systems that take a cluster from bare machines to customer-ready, end to end • You will be managing machine lifecycle between tenants: join, wipe, verify, rejoin, reliably and at scale • You will be operating Kubernetes and Postgres across the fleet, keeping critical infrastructure healthy under real production load • You will be contributing to custom Kubernetes operators that power the control plane • You will be scaling clusters from tens of nodes to thousands, solving the problems that only show up at the edges of scale • You will be participating in on-call rotations and responding to production incidents with the depth of knowledge to resolve them quickly Skills / Must Have: • A track record of impressive technical work you can speak to in depth, the years matter less than the quality of the work and its real-world impact • 2+ years of on-call experience for critical production services • Deep Kubernetes experience, not just consuming it but understanding what is happening underneath • Strong Linux fundamentals across kernel, cgroups, containers, networking, and storage • Experience operating databases, monitoring, CI/CD, and cloud infrastructure at scale • Familiarity with fleet management and capacity planning Desirable Skills: • Experience writing Kubernetes operators • Background in GPU infrastructure, HPC scheduling, or bare-metal hardware Benefits: • Meaningful equity • Fully remote across North America • Full insurance coverage for you and your dependants Salary: • $250,000 to $300,000 base salary