Amyloid formation, a hallmark of neurodegenerative disease and disorders, is attributed to the self-assembly of amyloidogenic proteins into insoluble, beta-strand rich fibrillar structures. The conformational heterogeneity of amyloids presents a major challenge in developing effective therapeutic strategies. In this study, we introduce an innovative rational design approach that combines novel computational methods with experimental validation to engineer a conformation-specific amyloid binder. By identifying specific regions on amyloid surfaces that exhibit conformational differences, we design peptides capable of selectively targeting and binding to distinct amyloid polymorphs. Initial peptide scaffold selection is performed using an automated alignment and clustering of natural protein backbones. Through biophysical characterization, we demonstrate the successful generation of conformation-specific peptide binders. These novel methods offer new tools to advance the field of amyloid biophysics and pave the way for the development of personalized therapies tailored to specific amyloid-related diseases. Additionally, our computational tools provide new opportunities for structure-based binder design and identification of conformation-specific binding sites in protein homologs.