The system's respective bulk phases are initially explored using the given parameter set, We then used the developed KVIK optimisation framework to train a reactive force field potential to describe the Li-Li, Na-Na and Li-Na interactions. The obtained ReaxFF parameter set can reproduce both systems' bulk and surface properties almost entirely within the margin of the calculated DFT standard deviation. We demonstrated that our proposed optimisation approach enables an efficient and accurate way to train reactive force field potentials in an automated fashion.