Senior Software Engineer

Microsoft•,

1d•$119,800 - $261,000

About The Position

Artificial Intelligence (AI) is only as fast as the compute infrastructure behind it, and Microsoft is adding Graphics Processing Unit (GPU) capacity at a pace few teams have ever had to match. You will join a fast-growing, fast-paced team building the operator layer that transforms raw GPU hardware into dependable, service-callable Azure capacity, working directly with Baseboard Management Controller (BMC) and Redfish management interfaces, Preboot Execution Environment (PXE) imaging, Data Processing Unit (DPU) provisioning, and network switch fabrics. You will own the point where architecture meets physical hardware, safely operating fleets of bare-metal nodes where every design decision must scale globally. If you want to help build the foundation supporting Microsoft's AI ambitions and grow quickly while doing it, this is the team. As a Senior Software Engineer on our GPU infrastructure team, you will design and build the operator layer that provisions, repairs, and manages bare-metal GPU servers, spanning BMC and Redfish management, PXE-based imaging, DPU initialization and provisioning, and network and switch adapters. You will help transform existing operator tooling into a concurrency-safe, service-callable boundary that automated workflows can invoke directly, eliminating entire classes of race conditions by design. This opportunity will allow you to develop expertise in distributed systems design at hyperscale, gain hands-on experience with cutting-edge GPU and DPU hardware, and rapidly expand your scope on a team that is growing quickly. Microsoft's mission is to empower every person and every organization on the planet to achieve more. As employees, we come together with a growth mindset, innovate to empower others, and collaborate to realize our shared goals. Each day, we build on our values of respect, integrity, and accountability to create a culture of inclusion where everyone can thrive at work and beyond.

Requirements

Bachelor's Degree in Computer Science or related technical field AND 4+ 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.

Nice To Haves

Master'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 Bachelor'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.
5+ years experience building or operating large-scale distributed systems or control planes (for example, orchestration, scheduling, or state-management services).
5+ years experience with Linux systems programming and fundamentals (switches, network interface cards).

Responsibilities

Design and own the architecture for provisioning and operator services that bring third-party graphics processing unit (GPU) servers online and keep them healthy, evaluating design options and documenting trade-offs for team and cross-team review.
Write extensible, secure, well-tested code for bare-metal automation — spanning firmware, imaging, and network configuration — and mentor other engineers on coding patterns, code review, and quality bar.
Serve as a designated responsible individual (DRI) on a rotational on-call basis, resolving live-site incidents within service level agreement (SLA) targets and driving root-cause fixes to prevent recurrence.
Apply artificial intelligence (AI) tools and practices across the software development lifecycle (SDLC), while taking responsibility for the quality and safety of AI-generated designs, code, and other assets.
Build the automation, telemetry, and monitoring needed to safely deploy and operate GPU fleets at scale, targeting zero-touch provisioning and rapid detection of failures.