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Tier-1 brand and metro location increase density, but senior, specialized AI/LLM QA reduces applicant pool.
QA fundamentals are transferable, but AI/LLM testing, RAG and embeddings expertise raise domain specificity.
Explicit 7+ years, leadership requirement, and many mandatory technical and AI/LLM testing tool requirements.
Lead and drive quality engineering strategies for both traditional software and AI/LLM-powered applications.
Manage and mentor QA teams across manual, automation, and AI testing, ensuring delivery of scalable, reliable software.
Evaluate emerging technologies and implement modern QA practices, continuous improvement, and automation frameworks integrating with CI/CD pipelines.
7+ years experience in Software Testing/Quality Engineering including end-to-end project delivery and team leadership.
Strong hands-on expertise in automation tools and languages: Python, JavaScript/TypeScript, Java, Playwright, Selenium, WebdriverIO.
In-depth knowledge of testing sectors covering UI, API, Database, AI/LLM, and related technologies such as RAG, embeddings, vector databases.
Hybrid work model requiring at least three days per week onsite in Gurugram/Noida/Pune locations.
Experienced in leading QA functions that cover manual, automation, and AI/LLM evaluations along with AI safety and security testing practices.
Strategic thinker familiar with agile methodologies, risk management, quality metrics, and integrating testing strategies in complex, multi-stakeholder environments.
Comfortable working in global, hybrid teams driving modern QA and continuous improvement initiatives in AI-enabled software contexts.