Software Engineer - Compute Infra ​/ HPC

** Overview*
* Microsoft AI is looking for experienced  
** Member of Technical Staff, Software Engineers - Compute Infra**  **/HPC
** to build the compute infra software that brings frontier AI compute online and keeps it healthy at global scale. You will work across cluster bring-up and automation, fleet and node lifecycle and health, and automated operations at global scale. The systems you build will transform newly delivered compute capacity into secure, observable, schedulable clusters and continuously recover usable capacity when hardware or software fails.

This is a hands-on software engineering role at the boundary of distributed systems and AI supercomputing. You will design control planes, APIs, workflow engines, state models, and hardware-aware automation for some of the largest GPU systems in the world. Rather than relying on manual intervention, you will turn recurring operational workflows and failure modes into durable platform capabilities that improve time to production, fleet availability, and researcher velocity.

** Microsoft AI*
* This role is part of Microsoft AI. Our Superintelligence team is a startup-like organization within Microsoft, dedicated to pushing the boundaries of artificial intelligence while maintaining a strong commitment to safety, responsibility, and human values.

Our mission is to build AI that amplifies human potential and empowers people around the world. We strive to deliver breakthroughs that advance science, education, productivity, and global well-being.

We are fortunate to partner with product teams that give our models the opportunity to reach billions of users and create immense positive impact. If you are highly ambitious, collaborative, and low ego, you will fit right in - come join us as we build the next generation of models and the computing platform behind them.

MAI employees are expected to work from a designated Microsoft office at least four days a week if they live within 50 miles (U.S.) or 25 miles (non-U.S., country-specific) of that location. This expectation is subject to local law and may vary by jurisdiction.

** Responsibilities*
* + Design and build distributed services, control planes, and platform APIs for the end-to-end lifecycle of AI compute clusters, from capacity ingestion and provisioning through certification, upgrades, maintenance, repair, and decommissioning.

+ Build foundational primitives that make new capacity enablement repeatable and secure by default, including cluster bootstrap, Kubernetes control planes, networking, identity and access, image distribution, secrets, infrastructure as code, and cluster metadata across Azure and partner clouds.

+ Own software systems that reduce cluster bring-up time by automating rack and node qualification, topology validation, scale testing, and the transition from newly delivered hardware to healthy, schedulable fleet.

+ Develop the node and fleet health platform that combines telemetry, health signals, diagnostics, and lifecycle state to detect, isolate, and remediate unhealthy hardware, hosts, networks, and storage with minimal human intervention.

+ Build policy-driven and agent-assisted automation for certification, maintenance, safe rollout or rollback of software and platform components.

+ Use production evidence, benchmarks, workload profiles, and fault injection to improve system architecture, efficiency, failure detection, recovery time, and the quality of health and readiness decisions.

+ Translate incidents and repeated operational work into durable software, stronger abstractions, automated guardrails, and clear ownership boundaries rather than one-off manual procedures.

+ Partner closely with researchers, hardware health, networking, storage, security, and datacenter teams to shape the long-term architecture of Microsoft AI compute infrastructure.

+ Provide technical leadership through design reviews, architecture decisions, code quality, mentoring, and execution of complex cross-team initiatives.

+ Embody our Culture ()  and Values () .

** Qualifications*
* *
* Required Qualifications:

*
* + Bachelor's Degree in Computer Science, Computer Engineering, Electrical Engineering, or a related technical field AND 4+ years of software engineering experience building production distributed systems, infrastructure platforms, or control-plane services

+ OR equivalent experience.

+ 4+ years of experience designing and implementing scalable software for cloud, datacenter, cluster, or fleet infrastructure using one or more general-purpose 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.

+ Demonstrated ability to debug complex behavior across service, control-plane, operating-system, networking, and hardware boundaries and turn findings into robust software improvements.

+ Experience leading projects across multiple teams and communicating…