Artificial intelligence (AI) is no longer just a topic of academic research: today it's a central part of products and services we use every day. From virtual assistants to recommendation systems or medical diagnoses, behind each application there are professionals who make it possible for AI models to work in the real world. One of the most in-demand roles in 2026 is that of the Artificial Intelligence Engineer. In this article we're going to see what they do, what their functions are, what skills they need and how you can train to work in this field.

What is an Artificial Intelligence Engineer?

An AI Engineer is the professional who designs, trains and implements artificial intelligence models to solve specific problems. While a Data Scientist usually focuses on exploring data and creating model prototypes, the engineer takes care of making those models work at scale in real products. Their work combines programming, mathematical knowledge and technological integration skills.

Main functions of an AI Engineer

• Design and train models: apply machine learning and deep learning techniques to solve problems like image classification, trend prediction or text analysis.

• Integrate models into applications: turn a prototype into a real service, for example, through APIs so it can be used in web or mobile apps.

• Optimize performance: adjust parameters and use resources like GPUs (high-performance graphics cards) so the models process large volumes of data.

• Monitoring and maintenance: make sure the model maintains its quality over time, detecting if accuracy drops and retraining it.

• Interdisciplinary work: collaborate with data, product, design and software development teams.

Skills needed

• Programming languages: mainly Python (with libraries like TensorFlow, PyTorch or scikit-learn) and in some cases R or Java.

• Databases and SQL: to query and manipulate data.

• Cloud computing: knowledge of platforms like AWS, Google Cloud or Azure to train and deploy models at scale.

• Statistics and mathematics: foundations of probability, linear algebra and calculus, applied to predictive models.

• Soft skills: communication, critical thinking and teamwork.

Job demand and salaries

According to the LinkedIn Jobs Report 2024, positions related to artificial intelligence are among the fastest-growing worldwide. In the United States, an AI Engineer can earn on average more than USD 130,000 a year. In LATAM, salaries range between USD 20,000 and 40,000 a year, varying according to the country and experience.

How to train as an AI Engineer

The path to becoming an Artificial Intelligence Engineer starts by understanding the fundamentals of AI and practicing with real projects. At Coderhouse you can find programs designed for different levels:

• Introduction to Artificial Intelligence Course — a first contact with AI, what it is and how to apply it.

• AI: Prompt Generation Course — how to interact with generative models to obtain quality results.

• Data Diploma — complete training that covers analytics, machine learning and applied deep learning.

If you'd like to keep exploring this topic, you can also read how to use AI to boost your professional profile.

Recommended Coderhouse courses

If you want to understand and apply artificial intelligence in your work, Coderhouse has programs for all levels:

• Introduction to Artificial Intelligence Course: to understand how AI models work and start applying them from scratch.

• AI Automation Course: to automate workflows with tools like n8n and Make, without needing to code.

• AI Engineering Course: for developers who want to integrate language models into real applications.

Frequently asked questions

What's the difference between an AI Engineer and a Data Scientist?

The Data Scientist focuses on exploring data and creating prototypes, while the AI Engineer takes those models to production, ensuring their operation at scale.

What programming language should you learn first?

Python is the most used in AI for its community, documentation and specific libraries.

Can you work in AI without a university degree?

Yes. Many companies value practical experience, projects and portfolio more than degrees. Intensive courses and online diplomas are a good starting point.

Which industries hire the most AI engineers?

Finance, health, retail, e-commerce, technology and automotive are sectors that lead hiring.

What projects can a beginner do to practice?

Simple examples: classifying images of cats and dogs, training a basic chatbot or predicting house prices with open datasets.

Conclusion

The Artificial Intelligence Engineer is the one who turns theory into practical applications that transform industries. It's a highly in-demand profile with great future projection. If you're interested in this field, you can start with introductory courses and then advance toward more complete programs to build your professional path in AI.

We recommend starting with the Introduction to Artificial Intelligence Course, then practicing with the AI: Prompt Generation Course and finally consolidating your profile with the Data Diploma.

Sources and references

• LinkedIn Jobs Report 2024

• Glassdoor – AI Engineer Salaries

• Statista – AI Market Worldwide

• Towards Data Science – Articles on AI & ML