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Constructing and executing reproducible workflows is fundamental to performing research in a variety of scientific domains. Many of the current commercial and open source solutions for workflow en- gineering impose constraints—either technical or budgetary—upon researchers, requiring them to use their limited funding on expensive cloud platforms or spend valuable time acquiring knowledge of software systems and processes outside of their domain expertise. Even though many commercial solutions offer free-tier services, they often do not meet the resource and architectural requirements (memory, data storage, compute time, networking, etc) for researchers to run their workflows effectively at scale. Tapis Workflows abstracts away the complexities of workflow creation and execution behind a web-based API with a simplified workflow model comprised of only pipelines and tasks. This paper will de- tail how Tapis Workflows approaches workflow management by exploring its domain model, the technologies used, application architecture, design patterns, how organizations are leveraging Tapis Workflows to solve unique problems in their scientific workflows, and this projects’s vision for a simple, open source, extensible, and easily deployable workflow engine.