Multilingual IT contact centers serve as vital operational structures for global corporations, facilitating engagement with geographically dispersed clientele across diverse languages, temporal zones, and technical complexities. Excluding their strategic significance, the mechanisms for scheduling and task allocation within these contexts have remained inadequately investigated within the classical project scheduling literature. Conventional frameworks addressing the resource-constrained project scheduling problem (RCPSP) neglect to incorporate dynamic constraints such as agent fatigue, linguistic alignment, shift-based availability, or the demands of strategic escalation. This systematic literature review integrates more than twenty years of advancements in RCPSP, leveraging hybrid metaheuristic methodologies—specifically Genetic Algorithms (GA) and Constraint Programming (CP)—to propose an innovative trajectory tailored to multilingual service operations. A case study is employed to corroborate the proposed model, demonstrating its potential to enhance SLA compliance, agent workload distribution, and language-specific support efficacy. This research provides a dedicated conceptual and algorithmic foundation for multilingual support scheduling—an area that has been predominantly preoccupied from the mainstream RCPSP discourse—thereby establishing a basis for forthcoming empirical validation and implementation in high-demand support environments.