Online education offers unprecedented scalability and accessibility to global learners from diverse backgrounds, but it often suffers from low engagement and poor long-term learning effectiveness. To address these challenges, we introduce AI Tutor, a reinforcement learning-based model designed to promote sustainable learning by optimizing both short-term and long-term learning outcomes. In the short term, AI-Tutor draws on cognitive theory to guide learners through a balance of acquiring new knowledge and reinforcing prior learning. In the long term, it models learner engagement to inform strategies that sustain motivation and reduce dropout. These enhancements enable AI-Tutor to provide personalized guidance that fosters both effective learning and sustained participation. Empirical evaluations on 23 million learning records from 33,700 learners show that AI Tutor consistently outperforms state-of-the-art baselines across engagement, knowledge retention, and final learning outcomes. Learning path analyses further reveal how AI-Tutor adapts its strategies to learners with diverse profiles, offering adaptive and human-centered support. Blogger's Review: AI Tutor's reinforcement learning approach provides a promising solution for sustainable learning in online education, optimizing short-term and long-term learning outcomes to improve learner engagement and learning effectiveness.