The exible job-oriented program model and distributed top-layer architecture described in this paper represent a novel top-layer approach to real-time software design and implementation, which can achieve portable, adaptable, fault-tolerant, and predictable high-value performance for a signi cant class of large-scale real-time systems with dynamic requirements, resources and constraints. Following a brief introduction to real-time software control issues and current layer-by-layer trends and limitations, we present an adaptive toplayer alternative to program modeling and control which can e ciently guarantee dynamic hard and soft requirements on a distributed platform, while providing best-e ort system values for arbitrary system state sequences. Practical and scalable control algorithms have been devised, analyzed, and tested, which strongly suggest that such an approach is viable even for dynamic large-scale and complex systems where conventional layer-by-layer alternatives fail. We also show how the proposed top-layer architecture might e ciently accommodate known levels of non-deterministic behavior within the platform and the environment. A musical ATLAS testbed is being developed to illustrate the feasibility of this approach.