Key responsibilities include :AI & Agentic Systems Implementation :- Design, build, and deploy Generative AI and Agentic AI solutions tailored for supply chain use cases (e.g., demand forecasting, scenario planning, exception handling, data monitoring).- Leverage technologies like LLMs, autonomous agents, reinforcement learning, and reasoning frameworks to power decision-making tools.- Lead the experimentation and operationalization of AI agents across planning, sourcing, logistics, and fulfillment domains.Data Engineering & Infrastructure : - Architect scalable data pipelines that ingest, transform, and serve high-quality data for AI/ML workloads.- Ensure robust data integration from ERP, Supply Chain systems, and third-party APIs (e.g., weather, risk).- Implement MLOps best practices to manage AI lifecycle: versioning, monitoring, retraining, and governance.