Austenitic steels used for components in high-pressure hydrogen storage systems in the automotive sector have to meet high requirements in terms of material properties and cost efficiency. The commonly used 1.4435/AISI 316L type steels fulfil the technological requirements but are comparatively expensive and resource-intensive. Lower alloyed steel grades are less costly, though prone to α-martensite formation and therefore sensitive to hydrogen embrittlement. Segregation-related fluctuations of the local element concentrations exert a strong impact on the austenite stability, thus controlling the segregation behavior can improve the austenite stability of lean alloyed steel grades, making them suitable for hydrogen applications. In this work, a novel approach for the optimization of alloy compositions with the aim of improving the homogeneity of the austenite stability is developed. The approach is based on combining automated Scheil–Gulliver solidification simulations with a multi-objective optimization algorithm. The solidification simulations provide information about the influence of the segregation profiles on the local austenite stability, which are then used to optimize the alloy composition automatically. The approach is exemplarily used for an optimization within the compositional range of 1.4307/AISI 304L. It is shown that a significant increase in the homogeneity of the austenite stability can be achieved solely by adjusting the global element concentrations, which has been validated experimentally.