Data · Role

AI Engineer

An AI engineer builds applications that use artificial intelligence models, such as machine learning models and large language models. This role appears in technology companies, banks, and consultancies.

In this role you might connect a language model to a company's own documents, deploy a model so an app can use it, or build a check on a model's output before users see it.

Background

The goal of an AI engineer is to make AI models useful inside real products. A model on its own does nothing for users. The AI engineer builds the software around it so that it runs reliably, responds quickly, and fits into the rest of an application.

Most of the work involves writing code that connects models to applications. You take a model, either trained in-house or provided by an outside company, and build the parts that feed data into it and handle what it returns. You also test how the model behaves, set up ways to monitor it once it is live, and fix problems when its output is wrong or too slow.

The main tools are Python and the libraries used to work with models, such as PyTorch or the interfaces provided by model vendors. AI engineers use cloud platforms like AWS, Google Cloud, or Azure to run models at scale. Relevant skills include programming, machine learning, and an understanding of how models are trained and where they fail.

The role sits between data science and software engineering. It is more technical and more product-focused than a Data Scientist role, which concentrates on building and training the models themselves. AI engineers rely on the infrastructure that a Data Engineer provides, and they work closely with a Developer to fit models into larger systems. In the Netherlands, technology companies, banks, and consultancies all employ AI engineers.

Sectors