AI Governance Lead

About Us
At Uber, we're not just moving people and things; we're building a global business grounded in integrity. Our Financial Risk Management (FRM) Advisory team is the backbone of that integrity, ensuring our financial reporting is accurate, trustworthy, and compliant with various regulatory requirements.
As AI becomes increasingly embedded in Uber's financial processes, the need to govern it rigorously has never been greater. As an AI Governance Lead on this team, you will help build the paved road—the frameworks, scaffolds, and control architectures that allow Uber's Finance and CAO functions to adopt AI confidently, with the right guardrails in place. Positioned at the cutting edge of technological advancement, Uber is committed to equipping our Finance teams with the tools and autonomy necessary to innovate, architect, and deploy sophisticated automated solutions. This role enables Finance to build securely, sitting at the intersection of emerging technology and financial risk, requiring you to work shoulder-to-shoulder with engineers, compliance technology teams, and senior Finance and CAO stakeholders to design controls that are both technically sound. This isn't just about checking boxes—it's about shaping what good looks like in a space where the standards are still being written.
Our Mission:
We ignite opportunity by setting the world in motion.
What We Do:
Uber's technology platform reimagines the way people and things move in cities around the world by connecting drivers, riders, and eaters. We offer a variety of services including:
Ride-sharing: Connecting riders with drivers for convenient transportation.
Delivery: Connecting consumers with restaurants and stores for food, groceries, and other deliveries.
Freight: Connecting shippers and carriers in the logistics space.
What you will do:
AI Control Scaffold Development: Partner directly with the engineering and FRM Compliance Technology team to design, build, and maintain reusable control frameworks and scaffolds for AI use cases that impact financial reporting. Translate requirements into implementable technical specifications that engineering teams can deploy and scale across the organization.
AI Use Case Evaluation: Serve as the FRM point of contact for evaluating new AI implementations within Finance and CAO. Assess ICFR risk exposure, determine whether existing controls are sufficient or whether new controls must be designed, and document evaluation findings in a repeatable, audit-ready format that supports both internal and external review.
Control Design & Implementation: