Chinook salmon (Oncorhynchus tshawytscha) are migratory fish that are highly valued for subsistence, sport, and commercial fisheries throughout their native range. Populations of Chinook salmon in western Alaska have exhibited long-term declines, leading to restrictions on harvests. Management priorities require greater resolution for genetic stock identification (GSI) than is available with current methods. We leveraged RADseq, TaqMan, and GT-seq data originating from multiple sources, collected through time, to develop a set of GT-seq panels containing 1092 single nucleotide polymorphisms (SNPs) that improved GSI resolution in western Alaska for at-sea and in-river sampling. We generated a dense linkage map to ensure that markers selected for panels spanned the entire genome. In addition, we identified multiple RADseq markers that were associated with sex; these aligned to a 5-centimorgan (cM) region on the sex chromosome. Finally, we developed a bioinformatic pipeline to streamline analysis of GT-seq data that is capable of genotyping microhaplotypes and paralogs, both of which can improve GSI resolution over traditional single-SNP data. Our panels and pipeline provide tools for management agencies to rapidly and easily analyze large-scale genotyping projects.