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AI-First QA Engineer (with Business Analysis Expertise)

AI-First QA Engineer (with Business Analysis Expertise)

CESIndia, India
1 day ago
Job description

About the Role

We are hiring a Functional QA Engineer who brings both business understanding and quality engineering skills . The role focuses on building quality from the first requirement using AI tools and copilots to design smarter tests, identify defects early, and simplify documentation.

You’ll work closely with product and development teams, using an AI-first approach to make testing faster, sharper, and more efficient.

Responsibilities

  • Use AI-based tools to plan, design, and run functional tests.
  • Create and maintain test scenarios from user stories or requirements using tools like ChatGPT, Testim, or Mabl .
  • Run manual and automated tests, identify flaky cases, and suggest areas for automation.
  • Use AI insights to spot defect trends and speed up root cause analysis.
  • Generate realistic test data with privacy-safe, AI-generated datasets.
  • Automate documentation, test reports, and test case updates.
  • Work with Product, Development, and DevOps teams to include AI-driven insights in sprints.
  • Try out new AI / ML testing tools and share recommendations.

Skills & Experience

  • At least 8+years of experience in Functional QA (manual + automation).
  • Good knowledge of QA processes, test planning, and test design.
  • Hands-on experience with tools like Selenium, Playwright, or Cypress .
  • Working knowledge of AI-powered QA tools such as Testim, Mabl, or Functionize.
  • Experience with ChatGPT, Copilot, Gemini, or similar tools for creating test cases or documentation.
  • Basic understanding of prompt design and how to guide AI tools effectively.
  • Scripting in Python or JavaScript .
  • Exposure to CI / CD platforms like Jenkins, GitHub Actions, or Azure DevOps.
  • Strong attention to detail and analytical skills.
  • Good to Have

  • Experience testing AI models or validating LLM responses.
  • Worked with AI-driven test management or low-code testing platforms.
  • Understanding of AI fairness and bias in testing.
  • Experience with QA dashboards or analytics using AI insights.
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