To accelerate alloy development, we designed an integrated, high-throughput method focused on parallelizing, miniaturizing, and automating each step: sample synthesis, preparation, characterization, and analysis. In this method, alloy test samples are built using laser metal deposition in 15-sample libraries that facilitates rapid and automated characterization by XRD, EDS, and EBSD. These analyses are coupled with machine learning to accelerate subsequent composition and processing decisions. We demonstrate this method for conventional alloy modification and to design a functionally graded material from 316L stainless to Ti-6Al-4V, without forming brittle intermetallic compounds. To mitigate intermetallic formation, a CALPHAD-based alloy design algorithm was developed to calculate phases formed and create a gradient path from 316L to Ti-6Al-4V, utilizing a third alloy as an additive. A sample library of discrete steps along the gradient alloy path have been printed and characterized to gain full understanding of microstructure development and develop a crack-free graded material.