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Senior Automation Engineer with 8+ years in test automation, API, and UI testing, leveraging AI-assi
Automation-focused IT Analyst with 7+ years' experience designing and delivering scalable test automation for enterprise applications. Expert in Selenium (Java), API testing (Postman, REST Assured), and Python scripting to build reusable frameworks, data pipelines, and utilities. Proven track record reducing regression effort by 30%, integrating test suites into CI/CD with Jenkins and Github, and validating end-to-end workflows across web and backend services. Strong collaborator in Agile teams, experienced mentoring junior testers and driving quality improvements through test strategy, defect management, and DevOps collaboration. Strong focus on innovation, leveraging AI-assisted tools (GitHub Copilot) and Generative AI concepts (Prompt Engineering) to enhance test design, automation efficiency, and defect analysis.
SASTRA Deemed to be University of Technology
Masters in computer application (MCA) · Allied Mathematical and Computer Application
August 1, 2018 – June 30, 2021
Muthayammal College of Arts and Science - Namakkal
Bachelor Of Computer Application (BCA) · Computer Application
August 1, 2015 – June 30, 2018
Sri Swamy Matric Hr.Sec, School - Namakkal
Higher Secondary · Mathematical and Computer Science
June 1, 2015 – May 31, 2015
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Cultural Fit Analysis
The candidate's diverse experience across functional and automation testing, coupled with a background in development, indicates adaptability and a broad understanding of the software development lifecycle. The proactive adoption of AI tools like GitHub Copilot and OpenAI API for automation suggests a forward-thinking and innovative mindset, which aligns well with a culture that values continuous improvement and technological advancement. Experience in mentoring and team leadership also points to a collaborative and supportive team player.
Soft Skills & Operational Fit
The candidate demonstrates strong collaboration skills, evidenced by working with developers and DevOps for defect resolution and knowledge sharing. Leadership experience in a small QA team indicates good task allocation and mentoring abilities. The focus on innovation with AI tools suggests a proactive and adaptable approach to problem-solving and process improvement. The candidate's experience in onsite production cutover support also highlights operational readiness and responsibility.