Jason Prodonovich
Senior Software Engineer Manager at Google
Greater Pittsburgh Region United States
Summary
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Rockstar🎓
Top SchoolJason Prodonovich is a Senior Software Engineering Manager with 11 years of experience building and leading front-end teams at Google, currently overseeing the Vertex AI Workbench frontend surface. He combines hands-on engineering—contributing to high-profile open-source projects like Kubeflow’s central dashboard, where he introduced TypeScript, Webpack/Express build tooling, and new UI components—with strong people management and product ownership. His background spans cloud AI UX, integrations with management APIs, and enterprise systems work (SAP, PL/SQL, ETL), enabling him to bridge data-science, partner, and operational needs. Jason has taught introductory computer science at the university level, reflecting a knack for clear technical communication and mentorship. Known for shipping pragmatic, maintainable front-end solutions, he often tackles both scoping and firefighting customer-facing issues end-to-end.
11 years of coding experience
9 years of employment as a software developer
MBA, Management, IT, MBA, Management, IT at The University of AkronBS, Computer Science, Philosophy, Business Administration, BS, Computer Science, Philosophy, Business Administration at University of Mount Union
Stackoverflow
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Github Skills (14)
javascript10
typescript10
typescripts10
user-interface10
react10
typescript-types10
webpacker9
webpack9
expressjs9
css9
kubernetes8
html8
kubernetes-pods8
machine-learning6
Programming languages (10)
Github contributions (5)
kubeflow/kubeflow
Feb 2019 - Nov 2019
Machine Learning Toolkit for Kubernetes
Role in this project:
Front-end Developer
Front-end DeveloperContributions:47 commits, 52 PRs, 638 comments in 8 months
Contributions summary:Jason primarily focused on front-end development tasks within the Kubeflow central dashboard. Their contributions involved refactoring the build stack to use Express and Webpack, incorporating TypeScript, and adding ESLint for code style enforcement. They also implemented new UI components, including the activities-list, and made improvements to the user interface, such as restructuring the dashboard layout and updating the navigation. Furthermore, this user refactored the iframe handling and integrated the user's information.
pythondata-sciencenotebookmachine-learningmlops
prodonjs/kubeflow
Feb 2019 - Nov 2019
Machine Learning Toolkit for Kubernetes
Contributions:197 pushes, 111 branches in 8 months
pythondata-sciencemachine-learningmlopskubeflow
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