Motivated by a practical situation in a digital transformation project, this paper considers a resource-constrained project scheduling problem with multiple modes, multiple skill types, and differentiated professional capabilities. In the proposed problem, each project activity has one or more alternative execution modes associated with a trade-off between processing time and resource consumption. In an execution mode, an activity requires a certain number of employees with specific skill types and required professional capabilities. A mixed integer programming model is developed to minimize the total project duration. Since this problem is NP-hard, an efficient immunoglobulin-based artificial immune system (EIAIS) algorithm with a new encoding and decoding scheme and novel components is proposed. The effectiveness of the proposed EIAIS algorithm is tested on randomly generated instances. Computational results show that the proposed EIAIS algorithm has better performance than the existing algorithms.