• Define and communicate the long-term vision for ML/AI applications and engineering, aligning with corporate strategy. • Partner with senior executives, product, and engineering leaders to prioritize initiatives and allocate resources effectively. • Oversee design, development and deployment of enterprise-scale ML/AI solutions, inference pipelines, and respective technical roadmaps. • Ensure operational excellence in ML/LLM Ops, including automation, observability, and lifecycle management in partnership with the AIML platform engineering team. • Champion adoption of cutting-edge techniques (Deep learning, recommendation engine architecture, graph neural networks, causal inference, LLMs, RLs, etc). Drive responsible AI practices, model interpretability, and compliance with regulatory requirements. • Build and mentor a high-performing organization of managers and senior engineers. Foster a culture of continuous learning, experimentation, and engineering craftsmanship. • Establish standards for security, scalability, and architectural integrity across ML/AI systems. Implement robust governance for data privacy, ethical AI, and risk mitigation.