About This Architecture

Multi-agent AI hiring system orchestrates six specialized agents through LangGraph on AWS to automate end-to-end talent acquisition. FastAPI backend coordinates Skill Agent for resume parsing, Verification Agent for credential validation, Suggestion Agent for job matching, Test Agent for assessments, Interview Agent for scheduling, and Upskill Agent for learning paths. Pinecone vector database stores resume embeddings and job descriptions for RAG-powered semantic search, while PostgreSQL maintains audit logs of hiring decisions and user actions. React dashboard provides HR teams real-time monitoring of agent workflows, candidate pipelines, and compliance metrics. Fork this architecture on Diagrams.so to customize agent logic, swap vector stores, or integrate additional data sources like LinkedIn and GitHub APIs.

People also ask

How do you architect a multi-agent AI hiring system with resume parsing, credential verification, and automated interviews on AWS?

Use LangGraph as head orchestrator to coordinate six specialized agents (Skill, Verification, Suggestion, Test, Interview, Upskill) with FastAPI backend, Pinecone for RAG-powered resume embeddings, and PostgreSQL for audit logs. This diagram shows the complete AWS architecture with React dashboard for HR monitoring.