Multi-agent AI system orchestrates autonomous hiring workflows using LangGraph to coordinate six specialized agents: Skill Extraction, Verification, Suggestion, Test Generation, Interview, and Upskill. FastAPI backend routes requests from a React dashboard through the HEAD ORCHESTRATOR, which delegates tasks to agents that leverage Pinecone Vector DB for RAG-based candidate matching and PostgreSQL for audit logging. This architecture demonstrates how HR teams can automate end-to-end talent acquisition—from resume parsing and skill verification via LinkedIn and GitHub APIs to bias-free interview generation using Fairness Libraries—while maintaining full transparency through audit trails. Fork this diagram on Diagrams.so to customize agent workflows, swap vector databases, or integrate additional HR data sources for your talent platform. The modular agent design enables incremental adoption: start with skill extraction and verification, then layer in interview automation and upskilling recommendations as your AI maturity grows.