At Meta, I performed privacy and security reviews for DataSwarm pipelines, auditing SQL queries for potential user data exposure before production. I also built Python automation to validate LLM responses, verify policy compliance, and collect quality metrics across AI evaluation workflows.
I've supported LLM training by reviewing model outputs, identifying edge cases, and providing structured feedback to improve accuracy, safety, and reliability. I investigate defects, document findings, and partner with cross-functional teams to strengthen release confidence for AI-powered products.
At Aqueous, I designed and implemented a WebdriverIO automation framework using JavaScript, Node.js, Mocha, Chai, and Axios. I integrated automated tests into GitLab CI/CD pipelines with Docker and tested REST APIs, MongoDB-backed applications, and mobile applications on iOS and Android.
Earlier at React Smart Development, I developed reusable UI automation suites and expanded test coverage for web applications. Across my work, I combine manual and automated functional, regression, exploratory, accessibility, performance, security, and privacy testing.
