Backed by Sequoia, Founders Fund and Redpoint.
About the role
Build and continuously enhance the risk management framework for AI and Agentic AI systems, including inventory standards, assessment methodologies, control design, and issue management. Inventory and map Nubank's AI use cases to surface gaps, materiality, and the most critical risks, and define prioritized mitigation actions.
What they're looking for
- Education: A bachelor's or master's degree in a quantitative field (computer science, data science, statistics, mathematics, engineering, or related)
- Strong technical foundations: Proficiency in Python, SQL, and modern ML tooling, familiarity with LLMs, RAG systems, prompt engineering, and AI agent frameworks
- Evaluation and testing: Experience evaluating and testing ML and generative AI systems, including custom evals, benchmarking, stress testing, and drift/degradation monitoring
- Risk management experience: Demonstrated experience in risk identification, control definition, and framework building, understanding of model risk governance principles and independent effective challenge
- Data skills: Experience working with large datasets and building dashboards and analyses to support risk visibility
- High agency and adaptability: Comfortable operating in ambiguity, synthesizing fragmented technical and business context into a clear view of how complex AI systems actually work, and making sound judgments without a complete playbook
More about this role
Nu serves more than 140 million customers, guided by a mission to fight complexity and empower people. The company has been leading an industry transformation through innovative products and human-centered services.
Proprietary technology and data at scale power Nu’s digital platform, built to promote financial access, advancement, and transparency. Its business model thrives on customer love and lower costs, feeding a flywheel of growth and profitability.
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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
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