About the job
Microsoft Azure’s Artificial Intelligence and High Performance Computing (AI/HPC) organization powers some of the world’s largest cloud native supercomputers used for frontier AI training, scientific computing, and large scale distributed simulations. Our team builds and operates hyperscale GPU clusters that consistently place Azure among global leaders in the Top500, MLPerf, and Graph500 benchmarks. By joining us, you step into the engineering core responsible for ensuring these systems remain reliable, performant, and ready for the next wave of AI innovation.
At this scale, interconnect fabrics are a first order reliability system that directly determines GPU availability, training throughput, and customer SLAs. As a Principal Supercomputing Operations Engineer, you serve as the technical authority and strategic owner for interconnect fabric operations across flagship AI supercomputing environments. You treat InfiniBand and GPU interconnect fabrics as a single end to end reliability domain, defining how they are operated, debugged, hardened, and scaled in production. This is a hands on, production first leadership role operating at the intersection of architecture, live operations, and reliability engineering.
You will lead the most complex and impactful fabric related incidents, making high stakes technical decisions under ambiguity while balancing availability, risk, long term correctness, and customer impact. Beyond resolving incidents, you define failure models, operational strategy, and systemic prevention mechanisms that reduce recurrence at fleet scale. Your impact multiplies through technical leadership: setting operational standards, influencing engineering direction across teams, mentoring senior engineers, and partnering deeply with platform, hardware, firmware, and service teams to drive durable reliability improvements.
You will architect and drive automation, diagnostics, and telemetry that materially improve operability and debuggability of interconnect fabrics, and author authoritative playbooks, TSGs, and escalation models relied on across the organization. Through your judgment, designs, and operational strategy, Azure’s largest AI platforms scale safely, predictably, and sustainably to meet the demands of next generation AI workloads.
Responsibilities
Serve as the technical authority and DRI for InfiniBand and GPU interconnect fabric operations across large scale AI supercomputing environments, ensuring sustained GPU availability, training stability, and SLA compliance
Lead and orchestrate complex, high severity fabric incidents end to end, including detection, triage, mitigation, recovery, and root cause analysis, making high impact decisions under ambiguity
Perform deep, multi layer systems debugging across InfiniBand, Subnet Manager, GPU interconnect, PCIe, GPUs, firmware, drivers, and OS layers to identify true root causes at fleet scale
Drive operational excellence and systemic prevention by identifying recurring failure patterns, defining reliability models and failure domains, and authoring authoritative TSGs, playbooks, and escalation frameworks adopted across teams
Architect and drive automation, telemetry, diagnostics, and tooling that materially improve detection, observability, debuggability, and mean time to mitigation, raising the operational bar for interconnect fabrics across the platform
Qualifications
Minimum
Bachelor's Degree in Computer Science or related technical field AND 6+ years technical engineering experience with coding in languages including, but not limited to, C, C++, C#, Java, JavaScript, or Python OR equivalent experience.
Ability to meet Microsoft, customer and/or government security screening requirements are required for this role. These requirements include, but are not limited to the following specialized security screenings: Microsoft Cloud Background Check: This position will be required to pass the Microsoft Cloud Background Check upon hire/transfer and every two years thereafter.
Preferred
Bachelor's Degree in Computer Science OR related technical field AND 10+ years technical engineering experience with coding in languages including, but not limited to, C, C++, C#, Java, JavaScript, OR Python OR Master's Degree in Computer Science or related technical field AND 8+ years technical engineering experience with coding in languages including, but not limited to, C, C++, C#, Java, JavaScript, or Python OR equivalent experience.
6+ years of experience operating large‑scale distributed systems, high‑performance computing (HPC), or artificial intelligence (AI) infrastructure in production environments
Demonstrated ownership of mission‑critical production infrastructure with direct impact on service availability, GPU workloads, and customer SLAs
Hands‑on experience operating and debugging interconnect fabrics supporting large‑scale compute workloads
Strong Linux systems knowledge with experience debugging low‑level infrastructure issues across operating systems, drivers, and services
Proven ability to reason across hardware, firmware, drivers, and software stacks to diagnose and resolve complex production issues