Data Engineering for Multimodal AI

Chapter 3. Platforms and Patterns for Multimodal AI Data Engineering

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Data engineering has shifted from building data pipelines to engineering intelligence infrastructure. With the rise of multimodal foundation models, data engineers are now responsible for constructing the context layers that power real-time, agentic applications.

This chapter equips you with the architectural mental models required to design and operate multimodal context systems. Rather than cataloging tools in a rapidly shifting ecosystem, we focus on three enduring platform archetypes including managed AI platforms, composable data architectures, and real-time streaming infrastructure.

Across these archetypes, we identify the recurring architectural patterns that every production multimodal system must implement, regardless of vendor or tooling.

To anchor this chapter, we’ll use the example of Revault, a digital-first investment platform operating across multiple regulatory jurisdictions. Its onboarding system combines identity ...