Derek Legenzoff
Principal Software Engineer at Microsoft
Seattle, Washington, United States
Summary
🤩
Rockstar🎓
Top SchoolDerek Legenzoff is a Principal Software Engineer in Seattle with nine years of experience building developer-facing AI and search products, currently focused on coding agents for GitHub Copilot. He blends product management and hands-on engineering from roles across Microsoft and Google, with a track record shipping Azure OpenAI and Cognitive Search features that help developers and data scientists adopt AI. Derek has deep expertise in performance optimization and ML integration—evidenced by contributions to popular Azure Search samples where he tuned indexing throughput, refactored async pipelines, and added detailed performance metrics. He’s also incubated AI tech with customers and startups, co-founding an AI/ML startup before returning to platform-scale product engineering. Known for bridging UX, backend scalability, and model deployment, he thrives on turning research prototypes into production-ready developer tools. His background in MIS and applied data science gives him a pragmatic, metrics-driven approach to building reliable AI systems.
9 years of coding experience
9 years of employment as a software developer
Master of Science (MS) Management Information Systems, Master of Science (MS) Management Information Systems at The University of Alabama
Stackoverflow
116reputation
3kreached
9answers
0questions
Github Skills (30)
asynchronous10
continuous-deployment10
exponential-backoff10
python10
async10
net10
dotnet10
indexing10
azure-machine-learning10
ml-deployment10
asp-net10
performance-optimization10
dotnet-core10
csharp10
azure-search10
Programming languages (10)
Github contributions (5)
Azure-Samples/azure-search-knowledge-mining
Apr 2019 - Jun 2022
Azure Search Knowledge Mining Accelerator
Role in this project:
ML Engineer
ML EngineerContributions:2 reviews, 116 commits, 58 PRs in 3 years 1 month
Contributions summary:Derek primarily contributed to the deployment and integration of a machine learning model within the Azure Search Knowledge Mining framework. They updated the UI template, standardized variable names, modified model outputs, and updated the inputs for the Azure Machine Learning (AML) custom skill. They also made minor adjustments to the web UI and corrected a bug related to graph rendering.
miningknowledge-miningknowledgeazureazure-search
Azure-Samples/azure-search-dotnet-samples
Apr 2020 - Aug 2022
Azure Search .NET sample code
Role in this project:Back-end Developer & Performance Engineer
Back-end Developer & Performance EngineerContributions:3 reviews, 36 commits, 14 PRs in 2 years 4 months
Contributions summary:Derek primarily focused on optimizing the performance of Azure Search indexing within the .NET sample code. Their contributions involved implementing and testing different batch sizes, and exploring the use of exponential backoff strategies to handle indexing failures. They refactored code to use asynchronous methods and also added performance metrics, such as MB/second, to assess the efficiency of the indexing process, demonstrating a strong focus on both backend development and system optimization.
dotnetazure-searchazure
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