Support the design and implementation of agentic AI / GenAI systems that assist in automating supply chain workflows.

Build and maintain backend services and integrations using Python and/or Java.

Contribute to multi-agent workflows, such as tool execution, routing, agent collaboration patterns, and task orchestration.

Assist in creating testing and validation strategies for AI systems, including evaluation datasets, regression testing, and behavior monitoring.

Help implement and improve knowledge base systems, including RAG pipelines, grounding strategies, and retrieval quality improvements.

Contribute to experimentation with:

lightweight fine-tuning approaches for small language models (SLMs)

reinforcement-learning-inspired improvement loops for NLP/GenAI tasks (where applicable)

Partner with product and domain teams to understand supply chain needs and translate them into working software.

Participate in code reviews, documentation, and operational support to ensure high-quality production systems.