AI and Agentic AI Risk Management Senior Specialist

Nubank•Miami, FL

1d•Hybrid

About The Position

Nu is a leading digital financial platform with a significant customer base across Brazil, Mexico, and Colombia. Our mission is to simplify financial services and empower individuals through technology and data intelligence. The Model Risk team is integral to managing the risks associated with our models and AI systems. We are establishing a specialized AI Risk Management function to address the unique risks posed by advanced AI, including Generative AI and autonomous agentic systems. This role will focus on AI quality, model and agent behavior, and the platform controls necessary for safe and reliable operation across various internal and customer-facing applications.

Requirements

A bachelor's or master's degree in a quantitative field (computer science, data science, statistics, mathematics, engineering, or related).
A track record developing or validating AI/ML models and systems, ideally with a background as an AI / Machine Learning Engineer transitioning into model risk, governance, or risk management.
Solid, current technical depth in AI/ML.
Proficiency in Python, SQL, and modern ML tooling.
Familiarity with LLMs, RAG systems, prompt engineering, and AI agent frameworks.
Experience evaluating and testing ML and generative AI systems, including custom evaluations, benchmarking, stress testing, and drift/degradation monitoring.
Demonstrated experience in risk identification, control definition, and framework building.
Understanding of model risk governance principles and independent effective challenge.
Experience working with large datasets and building dashboards and analyses to support risk visibility.
Comfort operating in ambiguity, synthesizing fragmented technical and business context into a clear view of how complex AI systems function.
Ability to make sound judgments without a complete playbook.
Ability to engage and align stakeholders across first and second lines of defense as a credible technical peer.
Strong written and verbal communication skills, with the ability to explain AI risk to both data scientists and regulators using appropriate language.
Advanced or fluent English proficiency for international collaboration and documentation.

Nice To Haves

Experience in a 2nd or 3rd line of defense.
Familiarity with regulatory Model Risk Management and AI frameworks (e.g., SR 11-7 / SR 26-2 / OCC 2011-12, NIST AI RMF, EU AI Act).

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 identify gaps, assess materiality, and pinpoint critical risks, defining prioritized mitigation actions.
Assess the effectiveness, proportionality, and sufficiency of first-line monitoring to ensure AI systems remain fit for purpose.
Perform independent technical assessments of 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 such as 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, evaluations, analyses, and playbooks (including AI-enabled automation) to enhance the speed, scale, and effectiveness of AI governance and validation.
Serve as a trusted advisor throughout the AI/ML lifecycle, evaluating new use cases for materiality and governance requirements before deployment.
Discuss and report AI risk status and independent opinions to stakeholders, including senior management and regulators.
Champion AI risk management as a strategic enabler of safe and scalable AI adoption.
Build AI risk literacy across engineering, product, and risk teams.
Work in a multicultural, diverse, and highly skilled environment.