Nubank is one of the largest digital financial platforms in the world, aiming to redefine financial services in Latin America. They are seeking a Senior Specialist in AI and Agentic AI Risk Management to define and enhance the risk management frameworks for AI systems, perform independent assessments, and develop governance tools to ensure the safe use of AI technologies.
Responsibilities:
- 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
- Assess whether first-line monitoring is effective, proportionate to model risk, and sufficient to keep AI systems fit for purpose over time
- Perform independent technical assessments across generative AI, and agentic workflows, covering data, assumptions, methodology, testing, behavior, and monitoring
- Assess risks in LLM-powered applications, including RAG pipelines, tool use, autonomy boundaries, model/agent quality, human oversight, and hallucination risk
- Identify and document model limitations, failure modes, and emerging AI risks, including drift, instability, fairness, and robustness concerns
- Influence first-line teams on platform architecture and embedded controls for the safe deployment and monitoring of AI
- Build Key Risk Indicators (KRIs) and metrics for continuous monitoring of AI risk
- Develop tools, evals, analyses, and playbooks (including AI-enabled automation) to improve the speed, scale, and effectiveness of AI governance and validation
- Serve as a trusted advisor across the AI/ML lifecycle, evaluating new use cases for materiality and governance requirements prior to deployment
- Discuss and report AI risk status and independent opinions to stakeholders, including senior managers and, where relevant, regulators
- Champion AI risk management as a strategic enabler of safe and scalable AI adoption, and build AI risk literacy across engineering, product, and risk teams