Senior Quality Assurance Automation Engineer

About the Role- We are looking for a highly skilled Tooling and AI Automation Engineer with 5+ years of relevant experience to join our Automation team—not in a traditional application testing but as a specialist focused on building internal tools, test intelligence platforms, dashboards, and AI-driven test enablement frameworks.
Required Skills:
• Proficiency in Java / Python.
• Experience in building REST APIs or microservices for internal use and building new testing frameworks from scratch.
• Strong understanding of test automation frameworks (e.g., Pytest, Playwright, Cypress, Selenium ).
• Solid Hands on experience in API Testing using Rest Assured , Mobile Automation using Appium and basics of Performance testing.
• Working knowledge or experience with Mabl, TestRigor, or any AI automation tool .
• Experience with GenAI or LLM integration for test case generation or failure analysis.
• Experience integrating tools with CI/CD pipelines (Jenkins, GitHub Actions, GitLab CI).
• Familiarity with databases (SQL, NoSQL) and working with test data at scale.
• Good in Debugging, Test Case planning, problem solving and logical thinking.
Key Responsibilities:
• Test Automation Development: Build and maintain robust, scalable test automation frameworks for API, web, and mobile platforms.
• Design, develop, and maintain internal tools that enhance automation capabilities, CI/CD integration, and test data visualization.
• Build intelligent dashboards for real-time reporting of test results, release quality metrics, and defect analytics.
• Develop AI/ML-based solutions to optimize test case prioritization, test suite reduction, flakiness prediction, and self-healing scripts.
• Integrate tools and dashboards with CI pipelines (e.g., Jenkins, GitHub Actions) and test frameworks (Selenium, Playwright, etc.).
• Work closely with SREs, and DevOps teams to ensure tools are scalable, performant, and well-adopted.
• Create APIs, microservices, or CLI tools that support testing workflows, artifact management, and defect traceability.
• Continuously evaluate new AI/ML advancements and incorporate them into test engineering practices