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About the role
Key Responsibilities: • Architect and own AIdriven QA platforms across enterprise programs, ensuring scalability, observability, and governance • Build, productize, and deploy AI Bots / AI Agents for testing, analytics, and quality decisioning • Define and drive the endtoend AI strategy and roadmap for the ETMS practice • Provide handson technical leadership in AI agents, GenAI architectures, and intelligent automation frameworks • Design enterprisewide LLM integration strategies across: Test automation frameworks • Internal QA tools • Managed QA platforms • enabling intelligent automation, AI observability, and quality governance • Establish AIdriven quality metrics and evaluation frameworks using ML metrics (precision, recall, F1, confusion matrix) • Lead evaluation, selection, onboarding, and governance of AI tools and platforms • Integrate AI solutions into CI/CD pipelines for predictive quality, analytics, and automation • Drive stakeholder communication and AI narrative building, translating complex AI capabilities into business value • Define data strategy and governance models for AIenabled QA solutions • Mentor and grow AI architects Must Have Tools • LangChain + LangSmith / LlamaIndex • DeepEval / RAGAS • MLflow / Comet ML • Scikitlearn metrics • Azure OpenAI / AWS Bedrock
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