Job Description
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 validation
API Testing: REST, GraphQL, Postman, Pytest, Karate
AI Application Testing: Chatbots, Summarization, RAG, Vector Databases (Pinecone, FAISS, Weaviate), AI Agents
CI/CD & DevOps: Jenkins, GitHub Actions, GitLab CI, Docker
Testing Types: Functional, Integration, Regression, Performance (Locust, JMeter)
Version Control: Git, GitHub, GitLab, Bitbucket
QA Practices: Test strategy, risk-based testing, automation coverage analysis, defect prevention
