The rapid growth of course-based online platforms has expanded access to learning in non-formal educational contexts. However, many existing systems primarily emphasize content delivery and transactional functionality, with limited pedagogical coordination between activity tracking, assessment, and learner guidance. This paper proposes a multi-layered architectural framework for orchestrating course-based online learning through a structured separation of content management, learning activity tracking, competency modeling, adaptive support, and credentialing. A key contribution of the proposed model is the distinction between content completion and competency mastery. While completion indicators reflect engagement, mastery estimation is grounded in assessment evidence aligned with formally defined learning outcomes. The architecture introduces an orchestration mechanism realized through distributed coordination across layers rather than through a centralized autonomous controller, positioning artificial intelligence as a supportive tool for assessment item generation and feedback provision. A functional web-based prototype, SoftLearner, has been developed to validate the feasibility of the infrastructure and learning layers. The higher layers are defined architecturally and provide a foundation for future empirical validation. The proposed framework contributes to the development of pedagogically oriented AI-supported systems in non-formal online learning environments and supports cumulative, competency-based recognition of learning outcomes within lifelong learning contexts.