We call this emerging field AI Engineering.
Can't agree more! I would be more interested in AI systems engineering to identify, understand build systems at intersections of data, algorithm and infra to get combined system into production serving to end users.
This transformation illustrates why ML has become the dominant approach: data-driven systems adapt to situations that programmers never anticipated, while rule-based systems remain constrained by their original programming.
This is critical milestone of enterprise systems, platforms transformation going forward. We started with mostly rule-based systems with special purpose programming languages, systems often needed specific logic, rule changes by specific programming language skills to maintain, support. However, with data-driven systems, system will adapt with evolving rule, patterns changes as needed with minimal supervision, validation testing and based on feedback loop mechanisms.