Architect and design scalable, production-grade AI/ML systems and data pipelines. Collaborate with stakeholders to identify and scope use cases for machine learning, deep learning, NLP, and computer vision. Lead the selection and implementation of AI/ML frameworks, platforms, and tools (e.g., TensorFlow, PyTorch, Scikit-learn). Guide teams in model development, training, evaluation, deployment, and monitoring in production environments. Define MLOps strategy for CI/CD, model versioning, retraining, and governance. Ensure solutions are optimized for performance, scalability, security, and compliance. Work closely with data engineers to ensure robust data pipelines, feature stores, and data quality standards. Serve as an AI thought leader within the organization, mentoring engineers and promoting best practices. Evaluate new AI technologies and platforms to drive innovation and maintain competitive advantage. Contribute to documentation, standards, and architecture governance.