Sheethal Hunsur Srinivas

I am an AI quality assurance and systems analysis leader with over a decade of experience in enterprise data systems, test automation, and quality engineering, currently serving as AI QA Lead at The University of Texas at Austin, where I lead the development of AI-powered systems for last-mile delivery exception handling and patient-facing AI assistants. In this role, I have led the development of an AI-powered multi-agent system for last-mile delivery exception handling, processing noisy logistics data and generating validated resolution actions with personalized customer communication, spearheaded a guardrail patient-facing AI assistant for electronic health records that achieved a thirty percent uplift in user engagement within the first three months of deployment, designed evaluation frameworks that reduced model output errors by twenty-five percent, built a Retrieval-Augmented Generation system for business analysts, validated AI outputs and governance controls increasing reliability by thirty-five percent, and drove cross-functional collaboration that improved component interaction efficiency by forty percent.

Prior to this role, I served as Senior Systems Analyst and Quality Lead at TECHNOVIZ LLC for over two years, where I led end-to-end, integration, regression, and UAT testing for large-scale enterprise data systems, improving system reliability by over thirty percent, designed comprehensive test strategies that reduced post-release defects by up to ninety-four percent, developed automated test scripts using ReadyAPI, Swagger, Postman, and SQL reducing manual testing effort by ninety-four percent, validated enterprise applications supporting over four hundred organizations, and built advanced data validation frameworks that streamlined error detection and improved QA process efficiency by forty percent.

Before that, I spent over five years at AE Business Solutions as Senior Systems Analyst and QA Lead, where I designed and executed comprehensive test cases for large-scale data systems, validated data workflows impacting approximately one million records across five integrated systems, identified and resolved ninety-four percent of critical data errors during testing, developed automated regression test workflows reducing manual testing effort by ninety-four percent, and improved overall data integrity by twenty-five percent.

Earlier in my career, I served as Quality Analyst at Quest Global and Apple, where I performed manual and automated testing for enterprise applications, developed automated test scripts using Squish reducing manual testing effort by up to ninety-four percent, implemented automation frameworks that saved approximately two weeks per testing cycle, and contributed to a ninety-five percent defect resolution rate using Bugzilla.

Across my career in AI quality assurance, systems analysis, and software testing, my work has been driven by a commitment to delivering high-quality, reliable systems through rigorous testing, automation, and cross-functional collaboration. Whether I am leading AI quality initiatives, building automated test frameworks, or validating complex data pipelines, I bring a strategic mindset, strong technical skills, and a dedication to excellence that ensures production-ready, scalable, and compliant solutions. I am proud of the work I have done throughout my career and excited to continue advancing AI quality assurance and systems analysis at The University of Texas at Austin.