AI Engineer - Hedge Fund

Our client, a growing Hedge Fund in Downtown NY with over $10 billion AUM is looking to add an AI Engineer to the team. You will help define the technical vision and roadmap for AI initiatives firmwide, with a focus on applied AI and agentic systems.

Responsibilities:

• Partner with key stakeholders to identify, prioritize, and accomplish high-impact AI opportunities.
• Design, build and deploy LLM-based products that solve specific business and investment workflows while generalizing into reusable, firm-wide AI capabilities.
• Architect and implement agentic AI systems capable of multi-step reasoning, planning, and tool execution.
• Develop and operate MCP (Model Context Protocol) servers and integrations to securely connect AI agents with enterprise data, APIs, and computational services.
• Own the full LLM and agent lifecycle, including prompt and system design, model selection, evaluation, deployment, monitoring, and continuous iteration in production.
• Lead applied AI R&D and rapid prototyping to move quickly from concept to production.
• Establish best practices for model development, deployment, evaluation, and responsible use of AI in production environments.
• Stay current with AI/ML advancements and apply emerging techniques to solve complex business and investment problems.
• Mentor and develop junior engineers and researchers.

Skills:

• 5+ years of applied industry experience building and deploying production AI systems.
• Advanced degree (Master's or Ph.D.) in Computer Science, Artificial Intelligence, Machine Learning, or a related quantitative field.
• Hands-on experience building and operating production-grade LLM applications, including evaluation, monitoring, and iteration in live environments.
• Experience with agentic and LLM frameworks, and a strong understanding of agentic design patterns.
• Experience designing and operating MCP (Model Context Protocol) servers or equivalent agent integration layers, enabling secure, standardized communication between AI agents and enterprise data, APIs, and services.
• Strong Python engineering expertise, including object-oriented design, microservices architectures, and REST API development.