About the Role- We are looking for a highly skilled Tooling and AI Automation Engineer (SDET-2) to join our Automation team—not in a traditional application development capacity, but as a specialist focused on building internal tools, test intelligence platforms, dashboards, and AI-driven test enablement frameworks. This role is ideal for someone who thrives at the intersection of testing, data engineering, and internal tool development, with a passion for empowering QA and Dev teams with intelligent systems and visual insights.

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 withSREs, 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.

Required Skills:
• Proficiency in Java - a scripting languages.
• Hands on experience in UI Testing (Java + Selenium) , API Testing (Rest Assured) and Mobile Automation Testing. (Appium - good to have)
• Working knowledge or experience with Mabl, TestRigor, or any AI automation tool.
• Strong understanding of test automation frameworks (e.g., Pytest, Playwright, Cypress, Selenium).
• Experience integrating tools with CI/CD pipelines (Jenkins, GitHub Actions, GitLab CI).
• Familiarity with databases (SQL, NoSQL) and working with test data at scale.
• Experience in building REST APIs or microservices for internal use.

Nice to Have
• Experience with GenAI or LLM integration for test case generation or failure analysis.
• Working knowledge of AI/ML libraries like Scikit-learn, TensorFlow, or transformers for testing-centric use cases.