Quant Modeling Lead - Corporate Controls - Vice President

As a Quant Modeling Lead within the Controls Room Team, you will design and build agentic systems that strengthen control monitoring, analytics, and decision support across the Firm.

Our mission is to work across agent architecture, workflow orchestration, tool and data integration, and the design of agent reasoning patterns to enable natural, multi-step problem solving.

This is a high-impact opportunity within our Control Management organization that comes with great visibility across all groups at the firm and the ability to impact thousands of employees by increasing efficiency in their day to day.

The Controls Room Team within Control Management works collaboratively with other control disciplines and oversees existing control functions as well as the development of new control functions and protocols.

The team's objective is to empower the three lines of defense with risk-based information to manage their control environment.

We achieve this by collecting, analyzing and monitoring firmwide risk-based intelligence into all lines of business and corporate functions.

The Controls Room gathers information from key business and technology partners in order to:


* Facilitate better decision making and actionable insights across the Firm.


* Create cost-effective and automated reporting; and


* Provide views into risk and issues.

Job Responsibilities:


* Serve as the Subject Matter Expert (SME) on agentic AI solutions, multi-agent architectures, and autonomous system design, providing strategic guidance and technical leadership across the organization.


* Design, architect, and implement dynamic multi-agent orchestration frameworks that enable autonomous agents to collaborate, coordinate, and adapt in real-time to solve complex control and risk management problems.


* Research, prototype, and productionize innovative agentic solutions leveraging state-of-the-art techniques in agent-based modeling, reinforcement learning, multi-agent reinforcement learning (MARL), and autonomous decision-making systems.


* Develop sophisticated agent coordination mechanisms, including communication protocols, task allocation strategies, consensus algorithms, and emergent behavior management for distributed agent systems.


* Build and deploy production-grade multi-agent systems that integrate seamlessly with strategic control management platforms, ensuring scalability, reliability, and real-time performance.


* Collaborate with Tech partners to architect agentic AI services using modern orchestration frameworks (e.g., LangGraph, AutoGen, CrewAI, or custom-built solutions) and deploy them within enterprise environments.


* Lead the development of autonomous agents capable of complex reasoning, planning, tool use, memory management, and self-improvement through feedback loops.


* Research data to discover insights and formulate relevant high-impact business questions that can be addressed through agentic AI and multi-ag...