Built backend services to monitor E2E test execution, providing real-time insights into passed, failed, and running test cases, along with visibility into the latest test runs. Developed AI-driven workflows that automatically analyzed test failures using test case documentation stored in a vector database. Enabled intelligent classification of failures into product, test script, or integration issues, with AI-generated fix suggestions. Reduced debugging and failure analysis time by ~80%, cutting daily effort from ~14 hours to under 2 hours through AI-assisted root cause analysis.