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Mid-level requirement, metro Bangalore location, and popular SDET role create moderate competition.
Strong GenAI/LLM evaluation and vector DB requirements make this role highly domain-specific and less transferable.
Explicit 5+ years SDET requirement plus specialized LLM, Python, and automation tech stack increases screening strictness.
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Develop and maintain automated test suites to evaluate generative AI/LLM systems for hallucinations, bias, toxicity, prompt injection, and multi-agent workflows.
Implement data quality assurance processes including statistical validation and auditing of AI data pipelines to prevent silent data failures.
Build scalable AI evaluation frameworks integrated into MLOps and CI/CD pipelines to enforce AI quality KPIs and release readiness.
5+ years of experience in a Software Development Test Engineer (SDET) role.
Expert-level Python skills including test automation and data analysis libraries (Pandas, NumPy, Pytest).
Proficiency in SQL for data validation and pipeline checks.
Familiarity with LLM evaluation frameworks (e.g. RAGAS, DeepEval), CI/CD tools (Docker, GitHub Actions, Jenkins), and API testing (Postman or REST Assured).
Experienced in end-to-end AI system validation including generative AI, vector databases, and multi-agent conversational workflows.
Skilled in building automated, scalable testing infrastructures tightly integrated with MLOps and continuous deployment environments.
Comfortable navigating complex AI evaluation metrics and data quality monitoring to ensure production-grade AI reliability and compliance.