Two modes of matching people with jobs prevail at present: hierarchical planning and distributed markets. Each has strengths and limitations, but few systems have been designed to exploit strengths corresponding to both. With evolving information technology, the job-matching process could be accomplished far more equitably and efficiently using Web-based markets within the firm. Intelligent agents offer excellent potential to help both potential employees and employers find one another in a distributed, electronic marketplace. But realizing this potential goes well beyond simply changing the rules of internal job matching or making agent technology available to job searchers. Rather, the corresponding markets and technologies must be designed, together, to mutually accomplish the desired results (e.g., efficient and effective matching) and conform to necessary properties (e.g., market clearing). In this chapter, we draw from Game Theory results to assess the feasibility of using two-sided matching algorithms to address this market-design problem. We also draw from current agent research to address the information technology dimension of the problem by implementing a proof-of-concept multi-agent system to enact, automate and support the corresponding market solution. This chapter integrates the key economic and technological elements required to design robust electronic employment markets. This chapter also presents preliminary results from a pilot experiment comparing performance for a human-based job assignment process to alternative market designs. These alternative designs can potentially reduce cycle-time and better match employees to job vacancies. However, the human-based process currently provides better rule conformance. Future research into Web-based internal job markets should address this shortcoming, among others.