4+ years of experience in applied data science or ML in a product environment, with demonstrated experience building agentic systems or autonomous agents MSc in Computer Science, Data Science, Mathematics, Statistics, Engineering, or a related field (or equivalent practical experience) Proven track record designing and implementing multi-step agentic pipelines, including LLM-based agents, tool use, planning loops, and memory mechanisms Hands-on experience with agentic frameworks such as LangChain, LangGraph, AutoGen, or equivalent Strong Python coding skills; familiar with Spark for large-scale, distributed data processing Experience with LLM APIs (e.g., OpenAI, Anthropic, Bedrock, open-source models) and prompt engineering for agentic use cases Experience performing rigorous model evaluation (baselines, cross-validation, error analysis) and defining evaluation strategies for agent behavior Strong communication and collaboration skills; able to work across engineering, product, and supply chain domain experts and iterate fast
