This research presents an AI-based Resume Analyzer capable of evaluating both PDF and video resumes using Gemini 2.0 Flash. The system employs Natural Language Processing (NLP) for textual analysis and Whisper for speech-to-text transcription and sentiment extraction from video resumes. Built using Python, Java, and Streamlit, the tool provides real-time feedback on communication skills, personality, and resume quality. The solution aids job seekers in self-assessment and enhances interview preparedness without relying on TypeScript. The crux of our AI Resume Analyzer is its job recommendation engine. With an intricate blend of collaborative filtering, content-based filtering, and hybrid recommender systems, it presents job opportunities that are a seamless fit with a candidate's skills and experience. This recommendation system operates dynamically to adapt to the ever changing job market, ensuring that the job opportunities presented remain relevant and reflective of the contemporary industry landscape. In light of the increasing emphasis on data security and privacy, we have implemented a robust framework to safeguard sensitive user information, complying with stringent data protection regulations.