Lead AI Quant Engineer

What you'll do

• Apply AI to improve system design, architecture, and team workflows.
• Identify and automate repetitive or error-prone processes using AI-powered improvements.
• Develop and deploy production LLM or agent-based systems with tool orchestration and retrieval.
• Build scalable, secure, and supportable platforms for moving research concepts into production.
• Implement CI/CD, automated testing, and model validation within a version-controlled environment.
• Manage model risk, data quality, and governance through human-in-the-loop controls and audit trails.
• Communicate technical trade-offs and AI limitations to senior stakeholders.

What we're looking for

• 4+ years of experience applying AI to improve system design and scale team workflows.
• Experience in quantitative engineering, data science, machine learning, or software engineering.
• At least three years of experience leading complex AI or quantitative systems.
• Expert-level Python skills and strong command of numerical methods, optimization, statistics, and risk analytics.
• Experience building production LLM or agent-based systems, including tool orchestration and reliability engineering.
• Strong architecture and distributed systems experience to move research concepts into secure, scalable platforms.
• Master's or Doctoral degree in a quantitative discipline, Computer Science, Engineering, Machine Learning, or a related field (preferred).
• Experience in asset management, quantitative equity, or investment-risk technology (preferred).