For a spectrally negative Lévy process with Laplace transform $ψ$, the $q$-scale function is characterized as the function whose Laplace transform is $(ψ(\cdot)-q)^{-1}$. It has applications in fluctuation theory, for example, exit problems and first hitting probabilities. It is also used in areas like ruin theory, risk theory, continuous state branching processes and optimal control. In this paper, we extend the scale function representation of Ivanovs (2021) from spectrally negative Lévy processes with phase-type jumps to the general case of matrix-exponential jumps. The extension is non-trivial because the probabilistic arguments employed by Ivanovs rely on an embedding to a Markov-modulated Brownian motion, a framework that does not accommodate the algebraic generality of matrix-exponential distributions. We overcome this limitation by embedding the Lévy process into a stochastic fluid process modulated by a rational arrival process (RAP), a class of continuous-valued Markov processes driven by orbit processes. This approach yields iterative schemes related to those of Ivanovs (2021) to provide a simple and explicit formula for the scale function. Our method gives the same fixed point when restricted to the phase-type case, and demonstrates the utility of orbit representations in analytical problems beyond the phase-type setting.