Varun Kumar Pusa

• Built TestPilot E2E, a comprehensive end-to-end testing suite developed with TypeScript and Playwright to automate complex user workflows. • Implemented automated API validation layers to ensure data consistency and backend stability across multiple application endpoints. • Improved regression testing efficiency by creating a modular framework of reusable test cases that reduced manual verification time. • Identified and documented technical bugs and critical edge cases, delivering detailed reports to support rapid engineering fixes. • Contributed to the software development lifecycle by integrating automated scripts that validate feature performance before production deployment. • Maintained an organized repository of technical test documentation and engineering insights to track product quality trends.

• Built VidQA Forge, an automated testing framework developed in TypeScript for evaluating AI-powered video generation platforms. • Designed comprehensive test suites to validate prompt-to-video accuracy, rendering consistency, and model performance under edge-case scenarios. • Identified and documented critical defects related to processing latency, failed video renders, and invalid input handling to improve reliability. • Implemented automated validation layers applying engineering rigor to monitor system performance and ensure the stability of the AI video generation pipeline. • Analyzed user feedback patterns from social channels to simulate real-world usage scenarios and expand the automated test repository. • Maintained technical documentation and engineering insights within the repository to support continuous quality improvements for AI-driven features.

• Developed PromptSight AI using TypeScript to evaluate AI-generated responses for relevance, coherence, and overall output quality. • Integrated OpenAI APIs to facilitate the comparison of multiple prompt variations and ensure consistent performance across diverse datasets. • Implemented automated scoring logic to streamline prompt engineering workflows and identify inconsistencies in Artificial Intelligence (AI) model behavior. • Tested core engine components to discover edge cases and document technical bugs related to API response handling and data accuracy. • Created comprehensive test suites to validate scoring algorithms and maintain high quality standards for AI-driven generated content. • Maintained detailed technical documentation and engineering logs to track the improvement of prompt evaluation accuracy and system reliability.