Requirements

• Bachelor's Degree in Computer Science, Computer Engineering, Electrical Engineering, or related technical field, plus 4+ years software engineering experience in distributed systems, infrastructure platforms, or control-plane services; or equivalent experience
• 4+ years experience designing and implementing scalable software for cloud, datacenter, cluster, or fleet infrastructure using languages such as Go, Rust, C++, C#, Java, or Python
• Experience with Kubernetes or comparable cluster-orchestration systems, Linux systems, public-cloud infrastructure, and infrastructure-as-code or declarative configuration
• Proven ability to debug complex system behavior across services, control-planes, operating systems, networking, and hardware, with ability to improve software robustness
• Experience leading cross-team projects and effectively communicating technical tradeoffs to both engineering and non-engineering stakeholders

Nice to Haves

• Master's Degree in Computer Science or related technical field with 6+ years software engineering experience; or equivalent experience
• Experience managing hyperscale compute infrastructure fleets with thousands of nodes, heterogeneous accelerators, or multi-cloud/datacenter capacity
• Expertise in cluster and node lifecycle systems including bare-metal provisioning, cluster bring-up, health checking, certification, maintenance, repair automation, capacity management, or decommissioning
• In-depth knowledge of Kubernetes internals and orchestration technologies (controllers, schedulers, autoscaling, kubelet, Cluster API, container runtimes, workflow engines)
• Experience building cloud foundational components such as virtual networking, CNI, private connectivity, DNS, workload identity, RBAC, secrets, image distribution, and infrastructure-as-code tools like Terraform
• Designing health, diagnostics, and remediation platforms using event-driven architectures, durable workflows, state machines, telemetry pipelines, automated decisioning, and safe recovery
• Low-level systems expertise with Linux kernels, device drivers, firmware, BMC/Redfish, secure boot/attestation, virtualization, or hardware health agents
• Experience with GPU/accelerator systems and high-performance interconnects (InfiniBand, RoCE/RDMA, NVLink, NCCL) and high-performance storage
• Ownership of production reliability and incident response, eliminating toil via automation
• Strong coding skills emphasizing clean, testable, maintainable, secure, well-documented software with focus on scalability and operability
• Ability to align senior stakeholders, mentor engineers, and lead multi-quarter technical initiatives from architecture through adoption
• Passion for learning evolving infrastructure technologies and improving reliability, efficiency, and usability of large compute systems

What You'll Be Doing

• Design and build distributed services, control planes, and platform APIs managing AI compute clusters through their entire lifecycle
• Create foundational primitives for repeatable, secure capacity enablement including cluster bootstrap, Kubernetes control planes, networking, identity and access, image distribution, secrets, infrastructure as code, and metadata
• Develop automation to minimize cluster bring-up time by qualifying racks and nodes, validating topology, scale testing, and transitioning new hardware to healthy, schedulable fleet
• Build node and fleet health platforms integrating telemetry, diagnostics, and lifecycle state to detect, isolate, and remediate unhealthy hardware and infrastructure with minimal human intervention
• Implement policy-driven and agent-assisted automation for certification, maintenance, and safe rollout or rollback of software and platform components
• Use production data, benchmarks, workload profiles, and fault injection to enhance system architecture, efficiency, failure detection, recovery time, and health/readiness decisions
• Transform operational incidents and repetitive workflows into durable, automated software capabilities and clear ownership boundaries
• Collaborate with researchers, hardware health, networking, storage, security, and data center teams to shape long-term compute infrastructure architecture
• Provide technical leadership via design reviews, architecture decisions, mentoring, and executing complex cross-team initiatives
• Embody Microsoft AI culture and values in daily work

Perks and Benefits

• Competitive salary range in the United Kingdom from £93,500 to £161,800 per year
• Eligibility for benefits and additional compensation depending on role
• Opportunity to work on some of the world's largest GPU systems and AI compute infrastructure
• Microsoft's commitment to equal opportunity employment and support for accommodations during the application process
• Hybrid work expectation: employees within a specified distance are expected to work on-site at least four days per week, subject to local laws