CAREERPILOT AI

The increasing competition in the employment market has created significant challenges for students and job seekers in preparing effective resumes, identifying relevant skills, and performing effectively in interviews. Existing career-support systems commonly address individual tasks such as resume screening, job recommendation, or interview preparation, while providing limited integration and personalization. This paper proposes CareerPilot AI, an intelligent career assistance system that integrates resume analysis, Applicant Tracking System evaluation, job-description matching, skill-gap identification, AI-based mock interviews, response evaluation, and personalized learning-roadmap generation. The proposed system uses Natural Language Processing, Large Language Models, semantic matching, and Retrieval-Augmented Generation to process user information and generate context-aware recommendations. A web-based architecture using Streamlit and FastAPI or Flask is proposed, with PDF parsing libraries for resume extraction and vector databases for retrieval-based services. The evaluation framework measures resume parsing accuracy, resume-job matching performance, skill-gap identification, interview-response evaluation, response time, and usability. The system is designed to provide an integrated digital career mentor that connects a candidate's current profile with target job requirements and subsequent preparation activities. Actual experimental results will be obtained after implementation and testing.