API: AI-Powered Virtual Interviewer– A Multi-Agent AI Framework for Company-Specific Interview Simulation and Placement Preparation

Authors:

M. Mallikarjuna Swamy, Dr. B. M. Vidyavathi, Md. Raheel, Md. Fahad, A. Likith

Abstract—This paper presents an AI-powered virtual interview system that enables students to prepare for company-specific recruitment processes through intelligent, adaptive simulation. The platform analyzes a candidate’s resume using Natural Language Processing (NLP) techniques and recommends suitable companies based on skill alignment and role requirements. Once a company is selected, the system generates a customized interview workflow that mirrors real recruitment stages such as aptitude tests, technical coding rounds, group discussions, and HR interviews. Machine Learning (ML), Computer Vision (CV), and speech processing algorithms evaluate the candidate’s performance across communication, reasoning, coding ability, behavioral cues, and domain knowledge. The system delivers structured, personalized feedback and improvement guidance, allowing students to practice continuously and bridge the gap between academic preparation and actual industry expectations. This AI-enhanced simulation framework provides a scalable, consistent, and highly realistic means for students to build company-ready competencies.

Index Terms— Company-Based Interview Preparation, Virtual Interview, AI Simulation, Campus Placement, NLP, Machine Learning, Behavioral Analytics.