About the Role

We are looking for an early-career Agentic AI Engineer to help build and evolve AI-powered systems that automate and improve supply chain workflows. In this role, you’ll work alongside experienced engineers and data scientists to develop agentic AI / GenAI features, integrate knowledge-based retrieval (RAG) patterns, and contribute to testing and validation approaches for AI systems that can behave in non-deterministic ways.

This is a strong opportunity for someone who is eager to grow in both software engineering and applied GenAI, and wants to work on real-world enterprise problems in supply chain and (optionally) life sciences.

Key Responsibilities

• 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, an