Damodar Kadiri

Dynamic Quality Engineering Leader and Healthcare IT SME with 15+ years of experience architecting end-to-end quality strategies for enterprise-scale Agile transformations. Expert in synchronizing global onshore-offshore delivery models to ensure seamless sprint execution and high-integrity production releases. A pioneer in AI-augmented testing, I leverage GenAI (Prompt Engineering), AccelQ, and GitHub Copilot to compress regression cycles and drive architectural excellence across complex, multi-vendor ecosystems

• Strategic QE Roadmap & Leadership: Defined and executed long-term QA roadmaps that align technical debt reduction with business growth. Managed $5M+ budgets and led global teams of 50+, maintaining a top-quartile retention rate through structured mentorship and performance-driven career pathing.
• Healthcare Domain Mastery: Deep Subject Matter Expertise in Healthcare IT, including Payer-Provider systems, Claims processing, and Regulatory Compliance (HIPAA). Led E2E quality initiatives for mission-critical systems and COUPA (CLM) implementations serving millions of users.
• Technical Innovation & Automation: Advanced practitioner in building robust automation frameworks using Selenium WebDriver, RestAssured, and UFT. Expert in implementing BDD/TDD methodologies within CI/CD pipelines (Jenkins/GitHub Actions) to achieve a 95% Defect Detection Efficiency (DDE).
• Stakeholder & Operational Excellence: Adept at influencing C-suite and technical stakeholders to foster a 'Quality-First' culture. Proven success in leading defect triages, UAT reviews, and Root Cause Analysis (RCA) to drive continuous process improvement.
• Led recruitment and development of a 50+ member global QA organization, maintaining a top-quartile retention rate through structured career pathing and upskilling programs
• Implemented AI-driven testing strategies that compressed regression cycles by 40-50%, significantly accelerating time-to-market for monthly release pivots.
• Championed automated gate-keeping and API-first testing, achieving a 95% Defect Detection Efficiency (DDE) for critical path functionalities