Hiring qualified employees is one of the most significant resources in organizations. However, the recruitment process can be time-consuming and costly. Recent research has shown that AI powered tools can be versatile in selecting suitable candidates in a short period of time. This conceptual paper explores the potential use of artificial intelligence (AI) in faculty hiring through AI model for video-data. By reviewing existing literature on AI-driven hiring, the study proposes a conceptual framework integrating video-based assessment to improve hiring efficiency and reduce bias. The proposed interaction stages for the AI model to rate the candidates are Candidate Introduction, Demo Class and Job Interview Questions. Furthermore, the Feature Engineering for proposed candidate interview for the AI model are: (1) Transcript Which include content and Linguistic style, (2) Audio (including voice tone and pitch) and (3) Visuals/Image (including body language). This research outcome contributes to developing the knowledge and operations of AI and ML in relation to HR practices.