Designs and leads globally distributed AI infrastructure that routes, prioritizes, and allocates computing capacity for Azure OpenAI and Microsoft Copilot. Responsibilities include coding, architecture, capacity optimization, reliability engineering, incident response, secure deployments, cross-team delivery, mentoring, and operating highly available services. The role also advances AI-assisted software development and responsible AI practices.
Overview
Responsibilities
Qualifications
Every time someone uses Azure OpenAI Service, their request needs to reach the right graphics processing unit (GPU), in the right region, at the right moment. Our team makes that happen. We build the platform that decides how AI traffic flows across Microsoft's global infrastructure, so services like Azure OpenAI and Microsoft Copilot stay fast and reliable. You'll join a supportive, connected team that keeps these experiences fair and dependable for every customer while making the most of every GPU we run.
As a Principal Software Engineer, AI Infrastructure on our team, you'll guide how AI requests are routed, prioritized, and matched to available computing capacity around the world. You'll shape the design of large distributed systems, work closely with partner teams across Microsoft and OpenAI, and help the engineers around you grow. This opportunity will allow you to influence the design of one of the largest AI platforms in the world, deepen your knowledge of large-scale optimization and efficiency, and grow as a trusted technical leader across many teams.
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.
Responsibilities
- Design - Own the overall design of how AI traffic and computing capacity are managed across regions. Guide design reviews and help the team weigh speed, reliability, scale, and cost when making choices.
- Coding - Write and review clear, secure, well-tested code for routing, prioritization, and capacity planning. Set coding practices that other teams can reuse.
- Implement - Work with product and program managers to turn the long-term vision into a dependable, step-by-step roadmap. Use feature flags and gradual rollouts to test changes safely, measure their impact, and roll back quickly when needed.
- Reliability and Supportability - Take part in the on-call rotation as a designated responsible individual (DRI) for critical AI services. Lead reviews after incidents and improve monitoring so issues are caught early and happen less often.
- Understand User Requirements - Partner with product, research, and infrastructure teams to understand what customers need as new AI models and capabilities launch. Work through shared dependencies cooperatively and make sure testing and support paths are ready before launch.
- Engineering Excellence - Help keep our services secure, private, and compliant through threat modeling, safe deployment checks, and clear records. Mentor engineers and share what you learn about building reliable systems at scale.
- AI-Native Development - Help the team use artificial intelligence (AI) tools and agents across the software development lifecycle (SDLC), from writing code and tests to investigating live issues. Follow Responsible AI practices and track how these tools improve quality and productivity.
- Embody our Culture and Values
Qualifications
Required Qualifications:
- Bachelor's Degree in Computer Science or related technical field
- AND 6+ years technical engineering experience building distributed systems with coding in languages including, but not limited to, C#, Java, or Go
- 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:
- Master's Degree in Computer Science or related technical field AND 8+ years technical engineering experience building distributed systems with coding in languages including, but not limited to, C#, Java, or Go
- OR Bachelor's Degree in Computer Science or related technical field AND 12+ years technical engineering experience building distributed systems with coding in languages including, but not limited to, C#, Java, or Go
- OR equivalent experience.
- 5+ years of experience running distributed services on public cloud platforms such as Microsoft Azure, Amazon Web Services (AWS), or Google Cloud Platform (GCP).
- 3+ years of experience with systems that route or schedule traffic, or that use optimization methods to allocate computing resources.
- Experience with Python, Docker, and Kubernetes.
- Experience with AI or machine learning (ML) infrastructure, such as serving models in production or managing GPU fleets.
- Experience leading projects across 3 or more partner teams, from design through launch and operation.
- Experience being on call for highly available services and measurably reducing incidents.
#AIINFRA
Software Engineering IC5 - The typical base pay range for this role across the U.S. is USD $142,800 - $274,800 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 $188,000 - $304,200 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.
Microsoft is an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to age, ancestry, citizenship, color, family or medical care leave, gender identity or expression, genetic information, immigration status, marital status, medical condition, national origin, physical or mental disability, political affiliation, protected veteran or military status, race, ethnicity, religion, sex (including pregnancy), sexual orientation, or any other characteristic protected by applicable local laws, regulations and ordinances. If you need assistance with religious accommodations and/or a reasonable accommodation due to a disability during the application process, read more about requesting accommodations.
Microsoft Redmond, Washington, USA Office
1 Microsoft Way, Redmond, WA, United States, 98052
Microsoft Bellevue, Washington, USA Office
Bellevue, United States
Microsoft Issaquah, Washington, USA Office
Issaquah, United States
Microsoft Kirkland, Washington, USA Office
Kirkland, United States
Microsoft Mercer Island, Washington, USA Office
Mercer Island, United States
Microsoft Sammamish, Washington, USA Office
Sammamish, United States
Microsoft Seattle, Washington, USA Office
Seattle, United States
Similar Jobs
Software • Quantum Computing • Metaverse • Infrastructure as a Service (IaaS)
Design and develop high-scale distributed AI infrastructure services supporting model training and inference on Azure Machine Learning. Build backend services using C#, Go, Rust, and C++ on Kubernetes and Docker. Operate reliable, secure, low-latency systems with 24/7 availability, provide operational ownership, collaborate with engineers and researchers, and provide technical leadership.
Top Skills:
Azure Machine LearningCC#C++Cloud SecurityDistributed SystemsDockerGoJavaJavaScriptKubernetesLarge Language ModelsMachine LearningPythonRust
Artificial Intelligence • Internet of Things • Semiconductor
Designs, builds, and operates large-scale AI compute infrastructure for training, fine-tuning, evaluation, and inference. Responsibilities include managing Kubernetes clusters, enabling CPU and GPU systems, optimizing scheduling and capacity, troubleshooting distributed infrastructure, and automating provisioning, upgrades, monitoring, and maintenance. The role partners closely with AI researchers and engineers to improve infrastructure reliability, scalability, performance, and developer productivity.
Top Skills:
Argo CdAws EksContainersCudaDcgmEfaGoGpuGrafanaHelmKubernetesLinuxNcclNetworkingNvlinkNvswitchPrometheusPythonPyTorchRaySglangStorageTensorrt-LlmTerraformVllm
Software • Quantum Computing • Metaverse • Infrastructure as a Service (IaaS)
Lead architecture and technical direction for reliability, observability, and operational health across a globally distributed AI platform. Design telemetry, health monitoring, capacity management, routing safeguards, overload protection, progressive delivery, fault testing, automated rollback, tracing, diagnostics, and recovery capabilities. Drive cross-team initiatives, mentor engineers, improve production practices, and build scalable infrastructure for AI inference and distributed services.
Top Skills:
Admission ControlAi/Ml Serving PlatformsAzureAzure MonitoringBackpressureCC#C++Capacity ManagementCloud InfrastructureDistributed SystemsDistributed TracingHigh-Performance ComputingJavaJavaScriptLoad BalancingPythonRetriesTelemetry
What you need to know about the Seattle Tech Scene
Home to tech titans like Microsoft and Amazon, Seattle punches far above its weight in innovation. But its surrounding mountains, sprinkled with world-famous hiking trails and climbing routes, make the city a destination for outdoorsy types as well. Established as a logging town before shifting to shipbuilding and logistics, the Emerald City is now known for its contributions to aerospace, software, biotech and cloud computing. And its status as a thriving tech ecosystem is attracting out-of-town companies looking to establish new tech and engineering hubs.
Key Facts About Seattle Tech
- Number of Tech Workers: 287,000; 13% of overall workforce (2024 CompTIA survey)
- Major Tech Employers: Amazon, Microsoft, Meta, Google
- Key Industries: Artificial intelligence, cloud computing, software, biotechnology, game development
- Funding Landscape: $3.1 billion in venture capital funding in 2024 (Pitchbook)
- Notable Investors: Madrona, Fuse, Tola, Maveron
- Research Centers and Universities: University of Washington, Seattle University, Seattle Pacific University, Allen Institute for Brain Science, Bill & Melinda Gates Foundation, Seattle Children’s Research Institute
