Join Microsoft's AI infrastructure team and contribute to the next generation of large-scale AI training and inference. Our AI Frameworks (AIFx) Networking & Systems Tools (NeST) organization builds foundational system software for Microsoft’s Maia accelerator platforms. We are expanding our end-to-end engineering capabilities in the India Development Centre, focusing on critical areas like control-plane services, host and device management, accelerator virtualization, Kubernetes-based infrastructure, and developer/debugger tools. This role is pivotal in designing and implementing scalable AKS/Kubernetes infrastructure for GPU and AI accelerator platforms, ensuring reliable operation at cloud scale.

Design and develop scalable AKS/Kubernetes infrastructure tailored for GPU and AI accelerator environments. Build robust services and automation for cluster provisioning, configuration, upgrades, and lifecycle management. Develop solutions for node lifecycle, health monitoring, failure detection, and automated recovery. Enhance infrastructure scalability, reliability, and availability across extensive accelerator fleets. Create Kubernetes integrations for accelerator discovery, resource management, scheduling, and workload enablement. Develop reliable software and automation for deploying, configuring, and managing accelerator infrastructure. Improve telemetry, observability, diagnostics, and operational readiness. Diagnose complex issues spanning Kubernetes, containers, Linux, networking, and accelerator infrastructure. Collaborate with cross-functional teams to deliver comprehensive solutions. Contribute to architecture reviews, engineering best practices, code quality, and mentoring. Apply AI-assisted engineering throughout the development lifecycle to boost velocity and quality, and leverage AI workflows for code comprehension, troubleshooting, and automation.

A Bachelor’s Degree in Computer Science, Computer Engineering, or a related technical field, or equivalent practical experience, is required, along with at least 4 years of industry experience. Proficiency in software development using languages such as Go, C++, C#, or Python is essential. Candidates should have experience building distributed systems, cloud infrastructure, or platform services, with hands-on expertise in Kubernetes and containerization technologies. A solid understanding of distributed systems concepts, including scalability, concurrency, state management, resiliency, and failure recovery, is expected. Proven experience developing reliable production software and debugging complex distributed systems is necessary. Strong design, problem-solving, and cross-team collaboration skills are key. Demonstrated ability to use AI-assisted software engineering tools and workflows to enhance development effectiveness, debugging, automation, and software quality is highly valued. The ability to rapidly acquire expertise in complex infrastructure technologies and apply that knowledge to production engineering challenges is also crucial.