This study employed a deductive approach to examine external HRM factors influencing job satisfaction in the post-pandemic hybrid work environment. Explores the intermediary functions of age, gender, and work experience in this particular environment. The data-gathering procedure consisted of conducting semi-structured interviews with carefully chosen 50 managers representing various sectors, industries, organizations, and professions. The applied approach was adopted to allow a systematic and unbiased investigation of the mediating variables. The study used SPSS 25 and Smart PLS 4 to analyze the model, enhancing understanding of HRM challenges in a constantly evolving workplace. The findings offer valuable insights for HR experts and businesses, highlighting the value of comprehending what methods HRM components influence job satisfaction to optimize employee well-being and productivity. The study provides applied recommendations designed for enhancing employee contentment in the AI-evolving professional atmosphere, shedding light on the importance of supportive leadership strategies, particularly during AI-triggered downsizing. Additionally, we welcome a new era to push forward in integrating and managing AI tools and technologies to automate decision-making and data processing. Results propose that Exogenous influences of human resource management (HRM) influence manager job satisfaction considerably. Specifically, downsizing caused by AI was found to have negative consequences, whereas diversity and restructuring have favorable effects. Gender was recognized as a crucial factor that influences outcomes, then age and years of experience have the most visible effect.