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- Define and ownAI/ML architecture for enterprise-scale solutions aligned with business objectives - Design end-to-end solutions involvingmachine learning, deep learning, generative AI, NLP, and computer vision - Collaborate with business stakeholders to translate requirements intoAI-driven architectures and roadmaps - Lead model lifecycle management includingtraining, validation, deployment, monitoring, and retraining (MLOps) - Provide architectural governance, best practices, and standards for AI implementations - Guide development teams on algorithms, frameworks, model selection, and performance optimization - Ensure AI solutions comply withsecurity, privacy, ethics, and regulatory requirements - Evaluate and recommend AI tools, platforms, and emerging technologies - Mentor data scientists, ML engineers, and architects .