Principal Software Engineer - M365 Storage Fabric team
About the job
- A Bachelor's Degree in Computer Science or a related technical field and at least 6 years of technical engineering experience coding in languages such as C, C++, C#, Java, JavaScript, or Python, or equivalent experience.
- A 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.
- Problem-solving experience involving system performance, resiliency, resource management, and operational excellence.
- Demonstrated ability to leverage AI-assisted engineering tools and autonomous coding agents to improve software development productivity, quality, and operational effectiveness.
- Ability to evaluate, validate, and refine AI-generated code, designs, tests, diagnostics, and recommendations while maintaining engineering ownership and accountability.
- Experience building infrastructure platforms, resource management systems, scheduling systems, load balancing systems, storage platforms, or large-scale backend services.
- Understanding of workload management, traffic engineering, fault tolerance, admission control, and capacity planning.
- Experience using telemetry, monitoring, and service health signals to drive automated operational decisions.
- Experience supporting services with rapidly changing demand patterns and large-scale customer workloads.
- Hands-on experience with cloud-native architectures and distributed platforms such as Azure or similar cloud environments.
- Experience with microservices and service-oriented architectures, event-driven systems, large-scale telemetry systems, and containerized and cloud-native environments.
- Experience building or supporting AI-powered services and high-throughput systems.
- Familiarity with AI workload characteristics, including bursty traffic, latency sensitivity, resource contention, and dynamic scaling requirements.
- Experience integrating AI-assisted engineering workflows into software development, testing, debugging, code review, and operational processes.
- Proven ability to drive technical alignment and influence engineering decisions across organizational boundaries.
- 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.
- A Master's Degree in Computer Science or a related technical field and at least 8 years of technical engineering experience coding in languages such as C, C++, C#, Java, JavaScript, or Python; or a Bachelor's Degree in Computer Science or a related technical field and at least 12 years of such experience; equivalent experience is also accepted.
About the company
Microsoft builds workplace software, operating systems and cloud infrastructure for consumers, businesses and government agencies, from small organizations to global enterprises. Microsoft 365 combines Word and Excel with Teams communication and Copilot AI features, while Windows runs PCs and Surface supplies the company's own computers. Azure rents computing capacity, storage and databases to build and run web applications. Microsoft also sells Xbox consoles and games, collecting revenue through software licenses, subscriptions, usage charges and product sales. Founded in 1975 by Bill Gates and Paul Allen, Microsoft is headquartered in Redmond, Washington.
Company Size
10,001+
Company Stage
IPO
Headquarters
Redmond, Washington
Founded
1975
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Simplify's Take
What believers are saying
- US corporate staff receive education support: eligible, approved graduate coursework qualifies for up to $10,000 annually.
- Cloud demand expands: July 2026 results showed Azure and other cloud services revenue grew 43% year-over-year in fiscal Q4.
- Investment has an earnings cushion: July 2026 results reported $155.2 billion consolidated operating profit for fiscal 2026.
What critics are saying
- Performance reviews include security: every Microsoft employee must discuss their security contribution with their manager.
- Office flexibility depends on the role: Microsoft's postings specify requirements ranging from fully remote to fully on-site.
- Cloud capacity faces local limits: Microsoft describes power-grid delays and water constraints affecting US datacenter expansion.
What makes Microsoft unique
- Hybrid customers stay within reach: Azure Arc manages servers across customer datacenters and competing clouds.
- Developer reach extends beyond Azure: Microsoft's GitHub hosts code collaboration alongside AI coding tools.
- Professional data widens its business: Microsoft owns LinkedIn's recruiting, advertising and workplace-learning network.
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Benefits
Health Insurance
Dental Insurance
Vision Insurance
401(k) Company Match
Professional Development Budget
Conference Attendance Budget
Flexible Work Hours
Remote Work Options
Growth & Insights and Company News
6 month growth
0%1 year growth
0%2 year growth
0%Investor Michael Burry, known for calling the 2008 housing crash, has warned that Microsoft and other big tech firms carry roughly $3 trillion in off-balance-sheet AI data-center liabilities. He said the companies are spending heavily because they assume they will get an oligopoly "too big to fail." Microsoft's capital spending in the June quarter was $41 billion, up 70% from a year ago. Its commercial remaining performance obligations, or contracted revenue not yet recognised, exceed $678 billion. Fourth-quarter revenue rose 18% to $90 billion, and net income rose 31% to $35.8 billion. Azure passed $100 billion in annual revenue. Shares are up 41% in three months. Analysts' consensus rating is "Strong Buy," with an average price target of $577.98.
Arena Physica has made Heaviside, its foundation model for electromagnetism, available on Microsoft Discovery, Microsoft's platform for agentic engineering. The company announced the move on October 13, 2026. Heaviside-1 has 350 million parameters and was trained on 250,000 3D field simulations. It predicts a design's full 3D electromagnetic field response in milliseconds, roughly 100,000 times faster than a traditional solver, and within a decibel of commercial accuracy. Traditional solvers can take hours or days per run, which makes design verification the main bottleneck. On Discovery, an agent can switch between Heaviside's predictions and a full-fidelity solver for final validation. Arena Physica expects strong uptake in semiconductors, including BGA packaging and SerDes interconnects. Discovery also offers audit logging and access controls to protect sensitive designs.
Venture capitalist Chamath Palihapitiya said power and physical infrastructure could be the lasting constraints in the AI race. He posted on X on Monday, after Microsoft announced its own silicon chips. Palihapitiya wrote that chipmakers will move up the stack while application companies move down it, so "everyone competes with everyone." He asked whether distribution, a data moat, or a physical limit such as power would support long-term margins. Elon Musk replied that scaling power, fast construction, cooling, networking, and batteries "is hard." Microsoft chief executive officer Satya Nadella said the company will scale its Maia chips to multi-gigawatt deployments starting next year. He said the Maia 300 delivers 40% more tokens per watt than leading GPU-based systems.
Peter Lee, who recently announced his departure as president of Microsoft Science, plans to join the Mercedes Formula 1 team as an AI advisor, he told Fortune. The role is newly created, and his title is still under discussion. Lee spent 16 years at Microsoft. At Mercedes, he will use AI to tackle car physics problems, break down data silos, build financial and predictive models, and advise on how regulators might govern AI in the sport. He is expected to sign a one-year contract with an option for a second. "I have always wanted to be a racer," Lee said. His exit follows other Microsoft departures this year, including Ryan Roslansky and Frank X. Shaw.
Microsoft has unveiled its latest homegrown Maia chips, part of an effort to rely less on outside semiconductor makers for its AI ambitions, Bloomberg reports. Elon Musk, meanwhile, wants to speed up chip development by testing as many as 10 new designs a year. Apple is also set to unveil its new smart home strategy, which seeks to fill a major gap in its ecosystem.