OverviewM365 Copilot inference is a high-impact engineering team advancing applied AI and large-scale machine learning across Microsoft. We design and operate the platform powering Microsoft 365 Copilot experiences.
Our team is operating at massive GPU (Graphics Processing Unit) scale across multiple regions and SKUs in global datacenters. We build the core LLM (Large Language Model) API (Application Programming Interface) , routing, capacity, and control plane services that turn that fleet into Copilot experiences.
We are hiring a Principal Group Software Engineering Manager to own GPU fleet health, capacity intake and planning, and automated model deployment for Copilot. This is one of the most strategic leadership roles in Copilot: every feature, experiment, and model launch flows through the systems this leader owns. You will lead existing teams, grow the org, and build the control plane that turns capacity management from a manual, ticket-driven process into an automated, self-driven platform.
You will own end-to-end GPU fleet health and capacity platform, establishing a single source of truth with strong observability across hardware, hosts, and workloads to drive utilization and reliability. Design and scale capacity intake, planning, and deployment reducing models time-to-production and meeting SLAs (service level agreement) for priority workloads through automation and data-driven operations.
Build a unified control plane that connects intake, planning, deployment, and fleet operations, enabling global optimization across cost, latency, compliance, and flexible model scaling (01 platform ownership).
Responsibilities- Build and lead a high-performing organization of engineering managers and senior engineers across capacity buildouts/automation, capacity planning, and the control plane.
- Set the strategy and roadmap for Copilot capacity management and the control plane.
- Drive execution across existing teams today, with a clear plan to grow the org as control plane scope expands.
- Partner deeply with Copilot, AI Core, Azure to align demand, supply, and COGs (cost of goods sold) for Copilot workloads.
- Own live-site, reliability, and operational excellence for the capacity surface area.
- Establish metrics and SLAs for intake latency, fleet utilization, automation coverage, and time-to-deploy; use them to guide investment decisions.
- Coach and grow managers and senior ICs (individual contributor); raise the engineering bar; recruit experienced platform leaders into the team.
- Represent capacity in executive reviews and cross-org leadership forums; communicate trade-offs between cost, speed, and reliability with clarity.
QualificationsRequired Qualifications:- Bachelors 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.
Other Requirements: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 Qualifications:- Masters Degree in Computer Science or related technical field AND 12+ years technical engineering experience with coding in languages including, but not limited to, C, C++, C#, Java, JavaScript, or Python
- OR Bachelors Degree in Computer Science or related technical field AND 15+ 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 people management experience.
- Experience as a manager of managers leading distributed-systems or platform engineering teams at scale.
- Demonstrated success building and operating large-scale distributed systems, control planes, orchestration platforms, or cloud infrastructure.
- Track record of taking a platform from concept to broad production adoption - design, staffing, execution, and live-site ownership.
- Systems thinking; able to identify and remove bottlenecks across intake, planning, scheduling, deployment, and operations.
- Experience driving multi-org programs and influencing partner teams without direct authority.
- Ability to translate ambiguous business needs into clear engineering strategy, priorities, and execution plans.
- Hiring, coaching, and people-development track record across multiple levels.
- Experience with large capacity fleets, AI/ML infrastructure, or large-scale inference or training systems.
- Experience with capacity planning, fleet management, or supply/demand optimization at hyperscale.
- Familiarity with Azure, M365, and AI workloads; understanding of inference and training cost models (COGS, utilization, throughput per GPU).
- Background building automation, control planes, or orchestration platforms from 01.
Software Engineering M6 - The typical base pay range for this role across the U.S. is USD $165,600 - $296,400 per year. There is a different range applicable to specific work locations, within the San Francisco Bay area and New York City metropolitan area, and the base pay range for this role in those locations is USD $220,800 - $331,200 per year.
Certain roles may be eligible for benefits and other compensation. Find additional benefits and pay information here:
https://careers.microsoft.com/us/en/us-corporate-pay
This position will be open for a minimum of 5 days, with applications accepted on an ongoing basis until the position is filled.
