QA Automation Engineer

Professional Summary – QA Automation Engineer Results-driven QA Automation Engineer with expertise in Python, Pytest framework, Playwright, and Selenium, applying Object-Oriented Programming (OOP) principles to design scalable and maintainable automation frameworks. Skilled in data handling using Pandas DataFrames for test data management and validation.Proficient in API testing and automation (REST & GraphQL) with tools like Postman and Pytest, ensuring robust backend validation. Experienced in testing AI-powered applications including chatbots, text summarization tools, and Retrieval-Augmented Generation (RAG) systems integrated with vector databases and AI agents.Hands-on experience in CI/CD pipelines (Jenkins, GitHub Actions, GitLab CI) for continuous testing, and in performance, functional, and integration testing to ensure high-quality releases. Strong QA mindset with a focus on defect prevention, risk-based testing, and automation coverage optimization. Core Competencies Automation Tools & Frameworks: Python, Pytest, Playwright, Selenium, OOP-based framework design (POM, Hybrid, Data-Driven)Data Handling: Pandas, NumPy for test data creation, transformation, and validationAPI Testing: REST, GraphQL, Postman, Pytest, KarateAI Application Testing: Chatbots, Summarization, RAG, Vector Databases (Pinecone, FAISS, Weaviate), AI AgentsCI/CD & DevOps: Jenkins, GitHub Actions, GitLab CI, DockerTesting Types: Functional, Integration, Regression, Performance (Locust, JMeter)Version Control: Git, GitHub, GitLab, BitbucketQA Practices: Test strategy, risk-based testing, automation coverage analysis, defect prevention