Description

You will contribute to developing a Knowledge Assistant for the Pro & Services organization, focusing on natural language understanding and agentic workflows.

Responsibilities

• Build, evaluate, and iterate on LLM-powered agents to support task execution, reasoning, and retrieval across structured and unstructured data.
• Collaborate with product managers and engineers to integrate intelligent systems into customer and associate-facing platforms.
• Own model evaluation and validation pipelines for LLM and RAG workflows, tracking performance and running ablation studies.
• Write clean, production-grade Python code and contribute to reusable components and pipelines.
• Apply analytical problem-solving to identify patterns, define rules, and optimize agent behaviors.

Required Skills

• 5+ years of experience in applied AI or PhD-level research.
• Strong programming proficiency in Python for building scalable ML/AI applications.
• Hands-on experience with LLMs, including prompt engineering, fine-tuning, or agentic architectures (LangGraph, AutoGen, CrewAI).
• Expertise in model evaluation for LLM systems, including designing metrics and running A/B tests.
• Experience with Vector Databases (e.g., FAISS, Pinecone) and LLM frameworks (LangChain).
• Familiarity with cloud platforms, specifically GCP.
• Experience with Git and VS Code.

Key Skills

Education

Any Graduate