Portfolio Manager, Agentic Systems

About the role

WorldQuant seeks a Portfolio Manager to manage risk and generate returns while utilizing cutting-edge agentic AI solutions within our Quantitative Trading divisions. This role integrates Portfolio Management with cutting-edge agentic AI technology.

Responsibilities

• Take risk, manage P&L, and make trading decisions within defined risk parameters while developing expertise in quantitative portfolio management principles
• Deploy and work with cognitive reasoning systems for quantitative modeling problems, leveraging planning, tool use, memory, reflection, and collaboration capabilities
• Adjust hyperparameters of reinforcement learning training processes to improve autonomous system performance and decision-making quality
• Contribute to deep learning model building for PM model layer applications specific to portfolio management objectives
• Build and customize agentic workflows and tools tailored to portfolio management needs and specific trading strategies
• Execute human-in-the-loop decisions and checks ensuring that traded strategies meet quant trading acceptance criteria

Requirements

• Advanced degree in a quantitative field (Computer Science, Mathematics, Physics, Statistics, Engineering, or related discipline)
• Minimum of 10 years of experience, PM experience is not required but preferred
• Familiarity with financial markets
• Experience with Python-based deep learning model development
• Willingness to learn portfolio management discipline, including P&L responsibility and risk management
• Hands-on experience with agentic AI frameworks
• Deep knowledge of the core capabilities of agentic systems: planning, tool use, memory, reflection, and collaboration
• Experience applying reinforcement learning methodologies to develop autonomous systems that learn and improve through policy optimization, reward modeling, and outcome-based feedback loops
• Ability to adjust hyperparameters and tune training processes for reinforcement learning systems

Qualifications

• Advanced degree in a quantitative field (Computer Science, Mathematics, Physics, Statistics, Engineering, or related discipline)
• Minimum of 10 years of experience, PM experience is not required but preferred

Skills

• Portfolio Management
• Agentic Systems Utilization
• Reinforcement Learning Tuning
• Model Development
• Custom Agentic Development
• Human-in-the-Loop Oversight

Benefits

• Base Salary
• Discretionary Performance Bonus
• Comprehensive Benefits Package

Pay

The Base Pay Range For This Position Is 150,000 USD.

Schedule

Full-time

Contact

To apply, please email your resume to [email protected]