AI Engineer - QA Automation

QA Automation Engineer – AI Focused
Role Description
We are looking for a strong QA Automation Engineer who combines hands-on automation expertise with practical use of AI tools and LLMs to improve the QA lifecycle. The ideal candidate should be able to use AI to accelerate test creation, expand coverage, generate test data, analyze failures, and improve automation—not simply automate existing regression test cases.
Key Responsibilities
Use AI/LLM tools to generate and optimize test cases, identify edge cases, create test data, and improve test coverage.
Leverage AI for test script generation, automation maintenance, defect analysis, root-cause analysis, and QA documentation.
Design and maintain automated testing for functional, API, integration, regression, and end-to-end testing.
Develop automation using Python/Java and Selenium, Playwright, Cypress, PyTest, or similar frameworks.
Explore and implement AI-driven approaches to improve QA efficiency, coverage, and test execution.
Integrate automated testing into CI/CD pipelines and collaborate with developers to troubleshoot and resolve defects.
Core Qualifications
3–8 years of QA experience with strong hands-on test automation.
Strong programming skills in Python or Java.
Hands-on experience using ChatGPT, Claude, GitHub Copilot, Cursor, or similar AI tools for software testing/automation.
Experience with Selenium, Playwright, Cypress, PyTest, or similar automation frameworks.
Strong understanding of API testing, SQL, Git, CI/CD, and QA methodologies.
Ability to identify practical opportunities to use AI to automate and improve QA processes, beyond traditional regression automation.
Preferred
Experience with AI-assisted test generation, self-healing automation, visual testing, intelligent test-data generation, or AI-based defect analysis.
Exposure to LLM/RAG applications or AI-powered testing tools.

Work arrangement
Yes