Matthew Booe is a Software Engineer II with 11 years of experience building ML-powered developer tools and backend services at Microsoft, focused on privacy-conscious integrations and telemetry-aware systems. Based in Redmond, he has driven features in high-profile open-source projects like the Azure CLI and its extensions—most notably integrating AI-driven example services and robust test suites for developer-facing workflows. He pairs back-end engineering with test automation and infrastructure improvements, regularly collaborating across teams to remove friction and scale solutions. An early-career leader who runs onboarding programs for hundreds of new hires, he balances hands-on coding with mentoring and process evolution. Off the clock he describes himself as a “part-time Jedi” and founded a community project (ufosc), hinting at a mix of technical curiosity and quirky leadership.
11 years of coding experience
1 year of employment as a software developer
Highschool Diploma, 4.0, Highschool Diploma, 4.0 at West Shore Jr/Sr High School
Bachelor's degree, Computer Engineering, Bachelor's degree, Computer Engineering at University of Florida
Contributions:6 reviews, 12 commits, 11 PRs in 2 years 1 month
Contributions summary:Matthew primarily contributed to the "az find" command module within the Azure CLI, focusing on its integration with an external service and telemetry. Their work included modifying the command to query an external example service, adapting the returned data, and implementing telemetry settings. They also removed potentially sensitive information from the telemetry data sent. Additionally, the user adjusted service URLs and updated the user ID used for rate limiting.
Contributions:1 review, 7 commits, 7 PRs in 8 months
Contributions summary:Matthew significantly contributed to the 'ai-examples' extension for the Azure CLI. Their work focused on integrating an AI-powered example service, including implementing functions to fetch, clean, and inject AI-generated examples into the help content. The user also developed comprehensive test suites and scenarios to validate the functionality of the extension, ensuring the correct integration and behavior of the AI-driven examples. Further contributions included refining telemetry, addressing bugs related to missing subscriptions and disabled telemetry, and enhancing the user experience with fallback mechanisms and rate limiting.
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