Senior Quality Assurance Specialist
2 weeks ago
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 Programming Language- 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
, Mobile Automation using
Appium(mandatory)
and basics of
Performance testing (good to have)
• 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
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