Pavlo Shevchenko
Lead Software Engineer at Gradle Inc.
Berlin, Germany
Summary
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Rockstar🎓
Top SchoolPavlo Shevchenko is a Lead Software Engineer based in Berlin with 10 years of experience building resilient distributed systems and developer tooling. He has progressed through hands-on roles at Gradle, where he led testing teams, improved Netty-based communication for remote Test Distribution agents, and drove observability features like test-flakiness detection and Test Distribution usage visualization. Pavlo has deep expertise in build and release automation—contributing to the widely used Gradle project by streamlining plugin configuration and test retry capabilities—and has led rebranding and consolidation efforts for enterprise plugins. His background includes cloud automation at AWS and tooling for large JSON/MongoDB analysis, reflecting a strong cross-domain systems mindset. Known for turning nuanced reliability problems into pragmatic engineering solutions, he also participates in hiring and OSS collaboration, blending technical leadership with hands-on implementation.
10 years of coding experience
6 years of employment as a software developer
Master of Science - MS, Computer Science, Master of Science - MS, Computer Science at Otto-von-Guericke-Universität Magdeburg
Github Skills (8)
build-tools10
gradlew10
gradle10
java9
cicd9
kotlin9
javas9
groovy7
Programming languages (8)
Github contributions (5)
gradle/gradle
May 2022 - Nov 2022
Adaptable, fast automation for all
Role in this project:
Automation Engineer / Build & Release Engineer
Automation Engineer / Build & Release EngineerContributions:31 reviews, 5 commits, 14 PRs in 6 months
Contributions summary:Pavlo primarily contributed to automating and maintaining the Gradle build process and related infrastructure. This is evident from the commits updating and configuring the Develocity Gradle plugin across multiple files. They consistently updated plugin versions and ensured compatibility across the build system, including smoke tests and core components. The user's work streamlined the build process and enabled the team to leverage features such as test retries and build scan capabilities.
pythongradlegroovyautomationjava
pshevche/drl-frameworks
Apr 2019 - Aug 2019
Comparison of several Deep Reinforcement Learning frameworks.
Contributions:129 commits, 12 PRs, 106 pushes in 3 months
deep-learningreinforcement-learningcomparisondeep-reinforcement-learningframeworks
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