AI and Agentic AI Risk Management Senior Specialist
crypto:applicationengineeringIC5Risk Management
Compensation
Not disclosed
About Us
Nu is one of the largest digital financial platforms in the world, with more than 122 million customers across Brazil, Mexico, and Colombia. Guided by our mission to fight complexity and empower people, we are redefining financial services in Latin America and this is still just the beginning of the purple future we're building.
Listed on the New York Stock Exchange (NYSE: NU), we combine proprietary technology, data intelligence, and an efficient operating model to deliver financial products that are simple, accessible, and human.
Our impact has been recognized by global rankings such as Time 100 Companies, Fast Company’s Most Innovative Companies, and Forbes World’s Best Bank. Visit our institutional page https://international.nubank.com.br/careers/
About the team
At Nubank we heavily rely on Data, Machine Learning, and increasingly on Generative and Agentic AI to drive our strategy and deliver the best experience and products to our customers. The Model Risk team plays a crucial role in ensuring the risks associated with our models and AI systems are understood and under control. We are now building a dedicated AI Risk Management capability to address the emerging risks of advanced AI — including LLM-powered and autonomous agentic systems — with a focus on AI quality, model and agent behavior, and the platform controls that keep these systems safe and reliable across internal and customer-facing use cases.
About the role
This is a senior, hands-on technical position. You will help define what model risk management looks like for AI and Agentic AI at Nubank — building and enhancing the frameworks, not just inheriting them. You will perform independent assessments of AI systems for quality, behavior, and robustness, and help design the guardrails and platform-level controls that govern their safe use. You'll act as a credible technical peer to first-line engineering and AI development teams, providing practical guidance on AI risk without slowing re