Automatic Hiring Process (HRBot) Using Agentic AI: A LangChain and LangGraph Implementation Framework

The recruitment landscape is changing fast, driven by a surge in job applications and the demand for hiring processes that are efficient, fair, and scalable. Traditional methods often depend on manual screening, which can be time-consuming and prone to bias. This paper introduces HRBot, an automated hiring system using Agentic AI with LangChain and LangGraph frameworks. The system automates job description generation, resume parsing, skill extraction, candidate ranking, interview scheduling, and communication. HRBot uses NLP and machine learning to evaluate candidates based on job requirements and semantic matching. Experimental results demonstrate improvements in recruitment efficiency, screening accuracy, and candidate quality while reducing hiring time and operational costs.