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Behind every intelligent system lies a team of professionals, each contributing a unique set of skills.
A recent visual I came across illustrates this beautifully, showing how Software Engineers, Data Engineers, and ML Engineers/Data Scientists intersect to bring AI agents to life.
Let’s break it down:
The Collaborative Core
While job titles may vary across organisations, the core responsibilities often align as follows:
Software Engineers ensure the system runs smoothly: building infrastructure, APIs, and maintaining security.
Data Engineers handle the lifeblood of any AI system—data. They build pipelines, set up databases, and ensure data quality.
ML Engineers & Data Scientists focus on models, prompts, evaluation, and productionizing the intelligence.
In the middle of this Venn diagram lies shared expertise: Git, observability, cloud, logging, and strong programming foundations.
Why This Matters
Many assume that building AI agents is mostly about machine learning.
But in reality, success comes from deep cross-functional collaboration.
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