Principal Software Engineer(M365 Storage Fabric team)
Microsoft
- Location
- China, Beijing, Beijing; China, Jiangsu, Suzhou; China, Shanghai, Shanghai
- Work model
- On-Site
- Level
- Principal
- H-1B history
- 2,066 approvals (FY2023)
- Posted
- 3h ago
Skills
About this role
Overview
Microsoft 365 (M365) is at the center of Microsoft's cloud-first, AI-powered productivity strategy, bringing together services such as Teams, Exchange, SharePoint, Microsoft Search, Copilot, and Office to empower organizations around the world. The M365 Storage Fabric team builds foundational platform capabilities that enable Microsoft 365 services to operate reliably, efficiently, and at hyperscale. We develop systems that optimize resource utilization, manage rapidly changing workload demands, improve service resilience, and support the next generation of AI-powered experiences. Our mission is to deliver dependable, scalable, and efficient infrastructure that helps Microsoft 365 customers achieve more while maximizing operational excellence across the platform. As AI workloads continue to accelerate across Microsoft 365, we are driving the evolution of intelligent platform services that can automatically adapt to dynamic traffic patterns, optimize infrastructure efficiency, and protect customer experiences at massive scale. 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
The team is looking for an experienced engineer to: Lead the design and development of large-scale distributed systems that manage resource allocation, workload execution, and service protection. Define and drive technical strategy for platform capabilities that improve reliability, efficiency, scalability, and operational excellence. Build intelligent, signal-driven automation using telemetry, health indicators, and real-time platform insights. Develop solutions that balance customer experience, infrastructure utilization, operational cost, and service performance. Drive innovations that proactively identify, mitigate, and prevent service disruptions. Partner with engineering teams across Microsoft 365, Copilot, Azure, and infrastructure organizations to deliver end-to-end platform solutions. Influence architecture, design, and engineering best practices across multiple teams. Mentor engineers and contribute to a culture of technical excellence and continuous improvement. Help shape how future AI-powered services are scaled, managed, protected, and optimized across Microsoft 365.
Qualifications
Required Qualifications: 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.
Preferred Qualifications
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 Bachelor's 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 equivalent experience. Deep understanding of distributed systems, concurrency, reliability engineering, scalability, and platform architecture. Experience developing and operating highly available backend services at scale. Demonstrated ability to lead technically complex initiatives across multiple teams and organizations. Solid problem-solving skills involving system performance, resiliency, resource management, and operational excellence. Demonstrated ability to effectively leverage AI-assisted engineering tools and autonomous coding agents to improve software development productivity, quality, and operational effectiveness. Ability to critically evaluate, validate, and refine AI-generated code, designs, tests,