Job Overview
Lead the development of autonomous AI agents that revolutionize investment workflows and client interactions. You'll build sophisticated multi-agent systems capable of independent research, portfolio optimization, and real-time market analysis, positioning our firm at the forefront of agentic AI in finance.
Key Responsibilities
- Design and implement autonomous AI agents for investment research, risk assessment, and portfolio management
- Build multi-agent architectures with specialized roles (research agents, trading agents, compliance agents)
- Develop agent communication protocols and collaborative workflows for complex financial tasks
- Implement reinforcement learning systems for adaptive agent behavior in dynamic markets
- Create agent orchestration frameworks managing task delegation, priority queuing, and resource allocation
- Integrate agents with existing trading systems, risk management platforms, and client advisory tools
- Collaborate with quantitative researchers to embed domain knowledge into agent decision-making processes
Required Qualifications
- Master's degree in Computer Science, Artificial Intelligence, or related field
- Experience developing AI/ML systems with focus on autonomous agents or multi-agent systems
- Strong background in reinforcement learning, decision theory, and agent-based modeling
- Experience with LLM-powered agentic frameworks (LangGraph, AutoGen, CrewAI)
- Proficiency in Python with deep learning frameworks (PyTorch, TensorFlow)
- Knowledge of distributed systems, message queuing, and microservices architecture
- Understanding of financial markets, trading workflows, or investment management processes
Technical Skills
- Core AI:
PyTorch, TensorFlow, reinforcement learning libraries (Stable Baselines3, RLLib) - Agent Frameworks:
LangGraph, AutoGen, multi-agent communication protocols - Programming:
Python, C++, distributed computing, async programming - Infrastructure:
Docker, Kubernetes, message queues (Redis, RabbitMQ), microservices - Data Processing:
Real-time streaming (Kafka, Pulsar), time series databases - Financial Tools:
Trading APIs, market data feeds, portfolio optimization libraries - Monitoring:
Agent performance tracking, decision audit trails, governance frameworks
Location:
Beijing
Application:
- Interested candidates may click to create your candidate profile.
- Or send CV in both Chinese and English version to , please indicate "Position - School Name - Major - Name" in the email title. For example: AI Agent
- UCB Finance - Bruce Lee