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Job Description
Structured overview of role & requirementsAbout This Role
Architect and develop an AI-native automation framework based on Playwright combined with LLM-powered agents for test planning, generation, execution, and self-healing.
Implement AI-output evaluation including hallucination detection, output scoring, and guardrail validation with integration into CI/CD pipelines (GitHub Actions, Azure DevOps, Jenkins).
Build end-to-end automated workflows and maintain golden datasets, supporting AI safety, bias, behavioral consistency tests, and data-migration validation.
Minimum Requirements
8+ years of experience in test automation or quality engineering, including 3+ years with AI/LLM-based systems or agentic automation frameworks.
Hands-on expertise in Playwright automation framework including fixtures, API testing, and complex workflow automation.
Proficiency in TypeScript and/or Python; experience using LLM APIs (Claude, OpenAI, GitHub Copilot).
BS/MS degree in Computer Science, Software Engineering, or related discipline.
Ideal Candidate Profile
Experienced in designing and industrializing automation frameworks used by multiple teams, not just executing tests.
Strong background in AI-quality engineering concepts such as hallucination detection, AI drift monitoring, and guardrail validation.
Proven ability to integrate automation solutions deeply into CI/CD environments and mentor engineers on AI-native quality practices.