Computer modelling is increasingly widely used in research into and predication of complex systems. My interest is the engineering of in agent simulation, which represents behaviours of complex system components such that the interaction of components in a computational environment results in emergent higher-level behaviours. Such models can be used for investigation of the possible mechanisms and controls that determine emergent forms. A key challenge of engineering complex systems is to demonstrate that the simulation achieves an appropriate analogue of observed behaviours by an appropriately similar behaviour: a challenge that we can consider as demonstrable fitness for purpose. Part of the challenge is that the agent simulation simplifies many levels and types of interaction – motivated by both computational feasibility and explanatory necessity. In this presentation, I will discuss our work on fitness for purpose and simulation engineering over the last two decades. I will then introduce recent attempts to address the challenge of uncertainty in complex systems modelling.