p>Preferred qualifications, skills and capabilities: Proficiency in Python programming with a strong grasp of object-oriented and functional programming concepts; experience applying Python in data processing, ML model development, and AI/LLM application development including prompt engineering and agentic workflow orchestration and hands-on experience with LLM orchestration frameworks (e.g., LangChain, LangGraph, LlamaIndex, or similar); familiarity with embedding models, vector databases (e.g., FAISS, Pinecone, pgvector), retrieval-augmented generation (RAG) pipelines, and evaluation frameworks for agentic systems.
Design and prototype retrieval layers (RAG, tool-augmented memory, knowledge base integrations) that agents rely on to take actions; ensure data quality and access controls are considered from day one of the PoC to avoid rearchitecting later and identify and mitigate risks unique to autonomous agents (unintended actions, prompt injection, cascading tool-call failures, data leakage) and establish guardrails and human-in-the-loop checkpoints early in the PoC to build a safe and auditable agent framework.