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Niche agentic-AI plus QA specialization reduces applicants, but metro location and mid-level seniority raise competition.
Role combines ML/LLM agent skills with deep quality engineering domain expertise, making cross-industry transferability limited.
Multiple explicit mandatory years and specific tech/QA/LLM integration requirements create stringent shortlisting filters.
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Design, develop, and maintain AI agentic workflows to transform enterprise quality artifacts into executable quality automation assets.
Build reusable prompt libraries, workflow templates, and integrate agentic workflows with enterprise tools like Jira, Zephyr, GitLab, Confluence, and Figma.
Support modernization and classification of existing automation assets, ensuring integration with current automation frameworks and maintaining regression testing capabilities.
Bachelor's degree in Computer Science, Engineering, IT, or equivalent practical experience.
2+ years experience in Agentic AI engineering and development for quality engineering.
5+ years experience in performance testing, test automation, SDET, quality engineering, or platform development.
Proficiency in Python and/or JavaScript/TypeScript; experience with test automation frameworks (Playwright, Selenium); knowledge of REST APIs, Git workflows, and CI/CD integration.
Experienced in integrating complex AI-first workflows with enterprise software development and testing tools and platforms.
Strong background in quality engineering covering functional, regression, integration, API, database, performance, security, and E2E testing domains.
Capable of designing AI outputs that are maintainable, reviewable, and scalable to enterprise quality automation ecosystems, including modernization of legacy automation assets.