We study large-scale service systems with multiple customer classes and many statistically identical servers. The following question is addressed: How many servers are required (staffing) and how does one match them with customers (control) in order to minimize staffing cost, subject to class level quality of service constraints? We tackle this question by characterizing scheduling and staffing schemes that are asymptotically optimal in the limit, as system load grows to infinity. The asymptotic regimes considered are consistent with the Efficiency Driven (ED), Quality Driven (QD) and Quality and Efficiency Driven (QED) regimes, first introduced in the context of a single class service system. Our main findings are: a) Decoupling of staffing and control, namely (i) Staffing disregards the multi-class nature of the system and is analogous to the staffing of a single class system with the same aggregate demand and a single global quality of service constraint, and (ii) Class level servi...