Responsibilities
- Design, build, and deploy AI/ML models for Supply Chain Planning (Demand Planning, Product Planning, Capacity planning, Inventory optimization, and production scheduling)
- Develop multi-agent and generative AI-powered systems (using LLMs and frameworks like LangChain, AutoGen, CrewAI) to enable real-time decision orchestration and intelligent automation
- Prototype intelligent assistants that interpret complex workflows, automate tasks, and generate data-driven recommendations for supply chain planners
- Implement autonomous agentic workflows that integrate insights across multiple enterprise systems (SAP, Blue Yonder, MES, Dynamics, etc.)
- Build and maintain scalable AI/ML pipelines using Python, Pandas, Neural Prophet, SQL, Spark, and AWS tools (S3, Lambda, SageMaker)
- Utilize containerization (Docker) and orchestration (Kubernetes) for deployment of multi-agent applications
- Apply MLOps best practices — CI/CD, model versioning, monitoring (Grafana, CloudWatch), and drift detection
- Work with Planning, Procurement, Manufacturing, IT, and Engineering teams to identify and prioritize use cases for automation and decision augmentation
- Present technical solutions, demonstrate prototypes, and communicate insights effectively to senior stakeholders
- Lead the exploration and adoption of Agentic AI frameworks for autonomous planning and execution in supply chain functions
- Stay current with emerging technologies in AI/ML, GenAI, and distributed intelligence systems
- Scale early-stage prototypes into enterprise-grade AI systems that deliver measurable operational efficiency
