Eldo Rajan

Background

About Eldo Rajan

With over 18 years of experience in QA Automation Frameworks, I specialize in creating scalable solutions that integrate the Software Testing Life Cycle (STLC) with the Software Development Life Cycle (SDLC). My expertise spans AI, TensorFlow, Kubernetes, Docker, LLMs, Vector Stores, GenAI, and Machine Learning, enabling innovation in software testing. Key Highlights: Automation Frameworks: Built frameworks for testing APIs, browsers, mobile, desktop, and Machine Learning applications, integrating tools like Selenium, Appium, TestNG, and Maven with CI platforms such as Jenkins and Bamboo. Delivered automation frameworks that reduced manual testing effort by 70%, enabling faster time-to-market for over 50 releases per year.* High-Volume Testing: Developed tests with 95% functionality coverage, 90%+ stability, and 4-8 hour runtimes, ensuring reliability across systems. Automated over test cases, achieving 80% reduction in test execution time and ensuring seamless overnight regression testing for large-scale systems.* ML Testing: Validated ML pipelines for data consistency, model performance, and bias detection, ensuring robust production deployment. Automated testing for over 20 Machine Learning models, achieving 99% accuracy in data validation and detecting drift in models.* LLM and GenAI Testing: Applied Large Language Models (LLMs) and Generative AI for test automation, enhancing test coverage and integrating vector stores for efficient data handling. Designed and executed over AI-driven test scenarios, improving test efficiency by 40% and increasing the detection of AI-specific edge cases by 25%.* Testing Strategies: Delivered robust strategies for functional, usability, and stress testing, with workflows ensuring scalability and fairness in AI/ML systems. Implemented comprehensive testing plans across 15+ enterprise products, reducing defect leakage by 30% and achieving scalability for systems handling over 1 million users.* Containerized Deployment: Deployed testing frameworks in Dockerized environments on Kubernetes, implemented auto-scaling CI pipelines, and optimized resources for software and ML solutions. Career Aspirations: I am driven to design and deliver innovative testing frameworks and AI-driven solutions that ensure the reliability of emerging technologies like Machine Learning, Generative AI, and LLM systems. I seek opportunities to contribute to cutting-edge projects where I can solve complex challenges, optimize quality processes, and empower teams to achieve scalable, efficient, and impactful results.