Cameron Moberg is a software engineer with a decade of hands-on experience and a current engineering role at Google based in Mountain View. He blends full‑stack Java client work—contributing notable features to the popular open-source RuneLite Old School RuneScape client—with backend and DevOps improvements to Apache Airflow, including Kubernetes/GCP integrations and DAG/web UI fixes. Comfortable across front-end UI/UX, game logic, API interactions, and cloud operators, he delivers practical features that span user experience to infrastructure. An early Truman State CS student who progressed through multiple Google internships into a full-time role, he brings both deep open-source collaboration and production engineering discipline. Unusually for someone with his tenure, his portfolio spans both gaming client UX enhancements and critical workflow orchestration tooling.
10 years of coding experience
Bachelor’s Degree, Computer Science, Freshman, Bachelor’s Degree, Computer Science, Freshman at Truman State University
Contributions:26 commits, 27 PRs, 12 comments in 1 year 6 months
Contributions summary:Cameron primarily contributed to the Runelite client, a Java-based application for Old School RuneScape. Their work involved both front-end (UI/UX) and back-end (game logic and API interactions) development. The user implemented features like an FPS overlay, XP tracker, and barbarian assault plugin. They modified existing UI components, added new overlay positions, and added new api widgets demonstrating a proficiency across various aspects of the Runelite client's codebase.
Apache Airflow - A platform to programmatically author, schedule, and monitor workflows
Role in this project:
Back-end & DevOps Engineer
Contributions:14 PRs, 23 comments in 2 months
Contributions summary:Cameron primarily contributed to the Apache Airflow project by implementing and improving functionalities related to Google Cloud Platform (GCP) integrations. They added operators for Google Kubernetes Engine (GKE), enabling users to create, delete, and manage Kubernetes clusters. Furthermore, the user fixed bugs related to DAG parsing and added features to the Airflow web UI, specifically the ability to delete DAGs. The user also worked on code to handle statsd configuration errors and improved the SSH operator.
monitorpythonschedulerapacheprogrammatically
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