• Designed and implemented tools to enhance velocity and productivity for Google Ads engineers.

• Maintained and improved Google's A/B testing framework for their ad serving stack, which is the largest set of A/B tests at Google and is used by hundreds of Google’s ads engineers on a daily basis in their engineering workflows.

• Expanded the depth of the A/B testing framework to include more ad types (e.g. mobile display ads and YouTube ads) by implementing new code paths and extending the mocked data coverage, which helped mitigate Google’s revenue losses from third-party cookie deprecation.

• Developed a new tool that empowers developers to efficiently test new features through a streamlined command-line interface, reducing the number of manual steps by 90%.

• Enhanced caching efficiency by integrating a staleness detection algorithm, resulting in a 75% decrease in average test run latency.