Senior Software Engineer - AI Diagnostics And Agentic Site Reliability Workflows at Microsoft
Miami-Fort Lauderdale Area United States
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Summary
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Mukund Sharma is a Senior Software Engineer based in the Miami-Fort Lauderdale area with a strong track record in runtime performance, garbage collection, and reliability engineering across Microsoft’s .NET runtime and performance tooling. With roughly four years of focused experience at Microsoft and earlier quantitative/engineering roles in finance and trading systems, he blends low-level systems expertise with applied data science and performance diagnostics. He has contributed notable fixes and optimizations to high-profile open-source projects like dotnet/runtime and PerfView—addressing GC internals, memory regressions, and real-time GC metrics. Mukund’s background in computational finance and large-scale data pipelines gives him a rare perspective on latency-sensitive, memory-constrained systems. Currently working on AI diagnostics and agentic site reliability workflows, he’s comfortable translating deep technical insights into tooling that improves observability and operational resilience. An understated strength is his history of coupling algorithmic rigor with practical engineering—whether in GC internals or trading-system simulators.
4 years of coding experience
8 years of employment as a software developer
Master of Science - MS, Data Science, Master of Science - MS, Data Science at University of Wisconsin Colleges
Electrical and Computer Engineering, Business and Computational Finance, Electrical and Computer Engineering, Business and Computational Finance at Carnegie Mellon University
PerfView is a CPU and memory performance-analysis tool
Role in this project:
Back-end Developer / Performance Engineer
Contributions:14 reviews, 4 commits, 13 PRs in 2 months
Contributions summary:Mukund primarily focused on improving the performance analysis tool's GC (Garbage Collection) related features. They added and fixed calculations related to heap counts, allocation rates, and pause times within the GCStats and related components. Additionally, the user refactored and optimized code, addressing issues related to POH (Pinned Object Heap) and overall GC data accuracy. They also integrated dynamic GC events to provide more real-time data.
.NET is a cross-platform runtime for cloud, mobile, desktop, and IoT apps.
Role in this project:
Back-end Developer
Contributions:96 reviews, 11 commits, 60 PRs in 9 months
Contributions summary:Mukund primarily focused on fixing and optimizing the .NET runtime's garbage collection (GC) features, specifically addressing issues related to memory allocation, heap management, and concurrency. Their contributions involved modifying core GC code, including adjustments to retry mechanisms, hard heap limits, and segment allocation. They also implemented and refined features related to CPU affinity and GC configuration, demonstrating a strong understanding of the runtime's internal workings and performance optimization techniques. The user’s contributions included adding new GC API methods and addressing a memory usage regression by fixing a typo.
dotnetruntimelinuxcsharpxamarin
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Mukund Sharma - Senior Software Engineer - AI Diagnostics And Agentic Site Reliability Workflows at Microsoft