Dalatea is building the AI copilot for bank risk teams. Think Harvey or Legora, but for the risk function of a bank.

We are automating complex banking processes end-to-end with AI agents across areas such as capital optimization, stress testing and regulatory reporting.

We are a small team led by people with experience at Oliver Wyman, Santander and the Bank of Spain, and backed by top-tier investors.

We are still early enough that the people joining now have a real opportunity to shape the product, the technology and the way we build the company.

Conditions

- Paid internship: €1,000 / month
- Internship agreement with your university.
- Potential opportunity to join full-time after the internship if it is a strong fit on both sides.

Role Overview

We are looking for a Full Stack & AI Intern who wants to build real product, not work on an artificial internship project. Your code will go into production.

You will work directly with our CTO and Founding Engineering, contribute to the real product roadmap and build software used by risk teams at banks.

You do not need to know anything about banking regulation before joining. You will learn that here. What matters much more is that you are curious, technically strong, willing to learn fast and excited by the idea of building things that real users depend on. You will work across the stack.

One day you might build a frontend feature or an API. The next you might work on an AI workflow, a data pipeline, a scraper, a chatbot or a cloud deployment. This is not an internship where you spend six months watching other people build. We want you in the arena.

What You’ll Do





- Build and ship features across our web application, working on both frontend and backend.
- Develop AI-powered functionality using LLMs, including chatbots, assisted analysis and automated generation of explanations and justifications.
- Build APIs, internal services and product workflows.
- Create data pipelines and scrapers to collect, transform and process information.
- Work with cloud infrastructure and deployments, with support from the engineering team.
- Write tests, open pull requests, review code and participate in the normal development workflow of a product engineering team.
- Work directly on tasks from the presente product roadmap.
- Use AI coding tools aggressively to improve the speed and quality of your work.
- Help us explore new ways of applying AI to problems in banking and financial regulation.
- Take ownership of increasingly complex problems as you demonstrate that you can handle them.

Must Have

- Currently in the final year of a Bachelor’s or Master’s degree in Computer Science, Telecommunications Engineering, Mathematics or a similar technical field.
- Ability to sign an internship agreement with your university.
- A solid foundation in programming.
- Experience with Python.
- Basic knowledge of Git and SQL.




- Ability to read and work with technical documentation in English.
- Curiosity and a strong willingness to understand how things work.
- Autonomy. When you get stuck, you try to solve the problem before waiting for someone to tell you what to do.
- High agency and a bias towards building.
- High standards for the quality of your own work.

Nice to Have

- Experience using AI coding tools such as Cursor, Claude Code or similar.
- Personal projects where you have built something from scratch.
- Experience with both web development and Python.
- Interest in AI, LLMs, agents and chatbots.
- Exposure to cloud infrastructure.
- Experience building APIs or data pipelines.
- A GitHub profile, portfolio or project you can show us.

We care much more about what you can build, how quickly you learn and how you approach problems than about having the perfect CV.

This Role Is Probably Not for You If You Expect

- An internship where you are given an isolated project that never reaches production.
- Someone to tell you exactly what to do step by step.
- To spend most of your time observing rather than building.
- Perfectly defined tasks with no ambiguity.
- To work exclusively on frontend, backend or AI without touching anything outside your preferred area.
- A large engineering organization with several layers of management and established processes for everything.
- To avoid responsibility because you are “just an intern”.
- To wait until you feel completely ready before shipping something.
- A slow learning environment with a predictable scope.
- To optimize for comfort over learning, responsibili

📌 Full stack (Madrid)
🏢 Dalatea
📍 Madrid