Across industry, applications involving Artificial Intelligence are shifting from task-specific to general purpose foundation models able to perform a diverse set of previously unseen functions with minimal instruction or additional training. To develop such a foundation model for engineering design, training must be completed at a meaningful scale on artifacts of prior product development, which can be multimodal and sparsely annotated. This work presents a sequence learning framework for training a foundation model on contextual relationships between function, form, and fabrication in engineering design. This learning method is demonstrated with a case study in absorbent product design.