The interview process is a critical gateway to professional employment, yet it remains heavily reliant on subjective human evaluation, scheduling constraints, and inconsistent assessment criteria. Candidates from diverse backgrounds often lack access to structured practice environments that can simulate real interview scenarios and deliver actionable, personalized feedback. This paper proposes an AI-Powered Virtual Interviewer system that addresses these limitations by delivering an end-to-end,