Key Strengths

Over 5 years of senior-level experience in Test Automation, specializing in hybrid Java/Python Selenium frameworks.
Proven expertise in AI/ML and GenAI testing, including LLM validation, prompt testing, and test case generation.
Strong background in API testing (Postman, Rest Assured, Swagger) and Performance Testing (JMeter, Load & Stress Testing).
Extensive experience with CI/CD integration (Jenkins, Git, GitHub) and DevOps practices.
Demonstrated ability to lead end-to-end QA lifecycles, implement 'Shift-Left' methodologies, and mentor junior engineers.
Achieved significant improvements in manual effort reduction (40%), test coverage expansion (30%), and sprint velocity (25%).
Certifications in Selenium with Java, Selenium Python Automation, and Software Testing further validate core skills.

Cultural & Operational Fit

Cultural Fit Analysis

The psychometric test score of 0 provides no objective data for assessing cultural fit aspects such as work attitude or team collaboration. The resume mentions cross-functional collaboration and mentoring, which are positive indicators, but these are unverified by the provided assessment results.

Soft Skills & Operational Fit

The psychometric test score of 0 provides no objective data for assessing logical reasoning, work attitude, stress handling, or team collaboration. While the resume mentions mentoring junior engineers and improving team sprint velocity, these claims lack independent verification through assessment data.

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Greeshma Gowda

Test Automation Engineer

https://www.opentalent.in/greeshma-gowda

Cambridge Institute Of Technology

Dubai, Dubai, United Arab EmiratesMember since April 29, 2026

https://www.opentalent.in/greeshma-gowda

About

Results-driven Senior QA Engineer with 5+ years of experience delivering high-quality software across audit, retail, healthcare, and e-commerce domains. Specialized in automation, API, performance, and AI/ML testing, with strong expertise in building scalable frameworks using Python, Java, Selenium and Pytest. Proven impact includes 40% reduction in manual testing effort and 60% faster regression cycles through automation and GenAI-driven QA strategies. Experienced in validating LLM-based applications, ensuring prompt stability, edge case handling, and reliable AI outputs for production environments. Strong hands-on experience in CI/CD integration (Azure DevOps, Jenkins, GitHub Actions), enabling faster and more reliable releases. Adept at managing the end-to-end QA lifecycle, from requirement analysis to UAT and production sign-off in Agile environments. Known for improving test coverage, optimizing workflows, and collaborating cross-functionally to deliver scalable, high-performance applications with zero critical defects. Core Expertise: Automation Testing | API Testing | Performance Testing | Manual testing | AI/ML GenAI QA | Test Framework Development | TestNG & Pytest | CI/CD | Agile QA UAE-based Automation Tester | Immediate Joiner | Open to relocate within UAE

Skills

JmeterAutomation TestingJavaPythonAgile MethodologiesAi MlPytestPostman

Education

Cambridge Institute Of Technology

computer science

August 31, 2014 – September 22, 2020

Key Strengths

Over 5 years of senior-level experience in Test Automation, specializing in hybrid Java/Python Selenium frameworks.
Proven expertise in AI/ML and GenAI testing, including LLM validation, prompt testing, and test case generation.
Strong background in API testing (Postman, Rest Assured, Swagger) and Performance Testing (JMeter, Load & Stress Testing).
Extensive experience with CI/CD integration (Jenkins, Git, GitHub) and DevOps practices.
Demonstrated ability to lead end-to-end QA lifecycles, implement 'Shift-Left' methodologies, and mentor junior engineers.
Achieved significant improvements in manual effort reduction (40%), test coverage expansion (30%), and sprint velocity (25%).
Certifications in Selenium with Java, Selenium Python Automation, and Software Testing further validate core skills.

Cultural & Operational Fit

Cultural Fit Analysis

Soft Skills & Operational Fit