I am a Senior Software Development Engineer in Test (SDET) with extensive experience designing, building, and maintaining enterprise-scale test automation systems for complex, distributed applications.

I am ISTQB certified and an Oracle Certified Java Developer, with a strong engineering background across Java, Python, JavaScript, and modern automation frameworks such as TestNG, JUnit, Pytest, Playwright, Cucumber, and Appium. My experience spans Web, API, database, and mobile automation, as well as non-functional testing including performance and load testing.

In my current role as an SDET at Vonage, I work closely with developers on large-scale, microservice-based systems, where test reliability, fast feedback, and accurate failure analysis are critical. My day-to-day work focuses on building robust automation frameworks, maintaining reliable test suites, and improving investigation workflows when tests fail.

Alongside my professional role, I actively design and experiment with AI-assisted approaches to test automation. This includes integrating AI APIs, designing AI-friendly automation architectures, transforming plain-text test plans into executable automation suites, and using AI to analyze test code, execution output, and service logs to produce clear, human-readable failure explanations. My focus is on using AI as an engineering tool, not a replacement for testing fundamentals—prioritizing control, determinism, and trust in automation.

I also bring a developer’s perspective to testing, with hands-on experience building Spring Boot and Spring MVC microservices, REST APIs, CI/CD pipelines (Jenkins, GitLab CI/CD), and cloud-based automation infrastructure on AWS. This allows me to approach AI-powered automation as a real system design problem rather than a prompt-only workflow.

In this course, I share practical, production-oriented techniques for applying AI to test automation responsibly—showing how to scale automation, reduce debugging time, and distinguish test issues from real service defects in complex systems. The content is based on real engineering challenges and solutions, not demos or theoretical examples.