AI architect vs AI engineer: the distinction orgs keep getting wrong
DavidLinthicum · x · 2026-10-08
David Linthicum highlights Mike Gibbs' breakdown of two often-conflated roles: AI engineers build, deploy, operate and troubleshoot AI systems, while AI architects decide what should be built, why it matters to the business, and whether the cost, risk, governance and value equation makes sense. He argues too many organizations rush into implementation before answering architecture questions — what problem, what data, what security/privacy/compliance risks, how to measure business value. AI success isn't just models, APIs, RAG pipelines or vector databases; it's the architecture decisions.
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