"How to make money with artificial intelligence skills?" is one of the most frequent searches in the sector, and it's no coincidence: AI created a layer of roles with salaries well above the tech average. This article compares the five highest-paid AI roles today, what each one does day-to-day, their reference salary ranges in LATAM, and what to study to get there.

The numbers vary according to country, seniority, and type of company, so the ranges are for reference and serve to gauge, not as a promise. The good news: almost all of these roles can be reached with focused training rather than with years of university.

Why these roles pay so much

Demand widely exceeds the supply of qualified talent. The WEF's Future of Jobs 2025 places AI and machine learning specialists among the fastest-growing roles in the world. And Stack Overflow's Developer Survey shows that the profiles that work with AI report higher compensation than the average.

1. AI Engineer

What they do: they build applications that use AI models: they integrate APIs, put together pipelines, optimize prompts, and take prototypes to production. It's the bridge between research and the real product.

Salary range (LATAM, reference): one of the highest in the sector, especially in remote mode for companies abroad.

How to train: programming foundations, APIs, and AI frameworks.

2. Machine Learning Engineer

What they do: they design, train, and deploy models. They work with data, define metrics, and monitor performance in production.

Profile: more mathematical and data-oriented than the classic AI Engineer.

If you come from the data world, the article about machine learning in companies and the roles it generates complements this landscape very well.

3. AI Product Manager

What they do: they define what AI product to build and why. They translate business needs into features, prioritize the roadmap, and coordinate technical and business teams.

Differentiator: they understand technology without necessarily programming, and they master strategy.

4. AI Architect

What they do: they design the architecture of large-scale AI systems: which models to use, how to integrate them, how to scale, and control costs. It's a senior role.

Profile: systems vision, experience, and deep technical judgment.

5. Prompt Engineer

What they do: they design and optimize the instructions the models receive to get reliable results. It combines logic, language, and experimentation.

Barrier to entry: the most accessible of the five, ideal as a gateway to the world of AI.

Comparison of the five roles

How to train at Coderhouse

For the most technical path, the AI Engineering course prepares you to build applications with AI. If you're drawn to the product side, the AI Products course addresses how to bring AI ideas to market. And if you're starting out, the Introduction to Artificial Intelligence course is the ideal base before specializing.

Frequently asked questions

Which of these roles is easiest to land without experience?

Prompt Engineer and, in some cases, junior AI Engineer roles usually have the lowest barrier. They serve as a gateway to then specialize.

Do I need a university degree for these positions?

Not always. Many companies prioritize projects, portfolio, and demonstrable skills over the diploma, especially in applied roles.

How long does it take to train for an AI role?

With focused training you can acquire solid foundations in a few months. The most senior roles, like AI Architect, also require accumulated experience.

Do these salaries apply working from LATAM?

Yes, especially in remote mode for companies abroad, where the salary gap plays in favor of regional talent. The amounts vary according to country and seniority.