Yet while the data is reliable by design, its business meaning is often implicit and difficult for AI systems to interpret, which prevents AI from reasoning over it reliably, safely, and at scale. You will work closely with product and engineering to turn complex, often ambiguous requirements into robust, scalable systems. What they lack is a way to work with it at scale. Over time, meaning gets buried in legacy systems, configurations, customization, and undocumented logic. The data still runs the business, but it can't easily be trusted, reused, or reasoned over consistently by modern software and AI. It runs the core business process of more than 90% of Fortune 500 companies. SAP has spent decades perfecting systems of record while AI is building systems of reasoning, and the real opportunity lies in connecting the two.
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