Big data and AI are transforming career counseling for college students by providing personalized career advice, real-time market intelligence, and smart decision-making. Conventional counseling is non-adaptive, while AI-powered systems scan academic history, skill sets, and industry trends to improve job matching. This research aims to maximize job guidance services with the aid of AI, in particular the BiLSTM model, for enhanced placement forecasting and job-matching accuracy. Through BiLSTM, the system increases resume-job match, skill-job fit, and employer-student matching. Validation on a test dataset of more than 10,000 students yielded an 18% increase in job-matching accuracy against baseline methods from 72% to 91% as the number of recommendations increased. Recommendations based on AI resulted in a 35% greater six-month job placement compared to traditional methods, with an 80% decrease in manual effort. The rate of satisfaction was a mean of 8.7, much higher than 6.5 for traditional career advice. These findings indicate how solutions through AI simplify job matching, increase placement efficiency, and enhance student career success.