The array design of multiple-input multiple-output (MIMO) systems in a line-of-sight (LoS) environment is investigated. Properly designed uniform array configurations at the transmitter (Tx) and receiver (Rx) can extract maximum spatial multiplexing gain only for a fixed transmit distance between the Tx and Rx arrays and for a fixed orientation of the arrays. However, such designs suffer from significant capacity variations when the position and/or orientation of the arrays is modified. To alleviate this, we examine robust, joint design of non-uniform Tx and Rx arrays, where the minimum capacity over a range of varying array positions and orientations is maximized. First, we show that, by leveraging convex relaxation, the joint Tx and Rx array design problem can be solved with convex optimization techniques in an iterative manner. Moreover, an alternative design method based on dynamic programming (DP) is proposed, which is shown to outperform the convex optimization approach. As the DP algorithm is quite demanding in terms of computational complexity, a modified DP-based algorithm is also proposed, where the Tx and Rx arrays are designed to have the same configuration. It is shown that the resulting non-uniform array configurations with the proposed designs outperform both uniform and non-uniform array designs of the literature in terms of the system robustness.