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Metro, mid-level Test Engineer title plus broad automation and AI skills increases applicant competition.
Strong Generative AI/LLM testing requirements make skills less transferable across non-AI industries.
Multiple mandatory automation, AI-testing, and CI/CD skills create strict shortlisting filters.
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Own end-to-end testing for AI/ML applications including test planning, automation development (UI using Playwright, API using REST Assured or Python Requests), execution, defect management, and reporting.
Validate AI model outputs, generative AI workflows, and LLM-powered applications, focusing on response correctness, consistency, bias, and safety.
Integrate automated test suites into CI/CD pipelines and mentor junior engineers on automation-first and AI-first Quality Engineering practices.
3-6 years of relevant experience.
Proficient in UI automation (Playwright) and API automation (REST Assured with Java or Python Requests).
Hands-on experience testing AI/ML or Generative AI applications including validation of AI outputs and familiarity with AI evaluation frameworks or libraries.
Strong SQL skills for database testing and experience integrating automation suites with CI/CD pipelines (e.g., Jenkins, GitHub Actions).
Experienced in comprehensive AI/ML quality validation including prompt engineering and AI evaluation techniques.
Able to independently manage test lifecycle with minimal supervision in Agile/Scrum environments.
Skilled in leveraging GenAI tools (ChatGPT, GitHub Copilot, etc.) to accelerate test case generation and debugging, indicating familiarity with modern AI-assisted QA workflows.