Quality Assurance Engineer

We are looking for a highly skilled Tooling and AI Automation Engineer with 3-8 years of relevant experience to join our Automation teamnot 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.

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 (mandatory)

-Mobile Automation using Appium(mandatory for 5+ years of exp).

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). (mandatory)

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