AI-Driven Investment Research Lead (Hybrid)

JW Michaels & Co.; San Francisco (CA); Hybride; USD 150 000 - 230 000; Plein temps

Résumé du poste

JW Michaels & Co. in San Francisco seeks an experienced AI professional to work directly with portfolio managers and research analysts.

You will own the development and deployment of AI-powered tools that enhance investment research. The role combines hands-on coding with close collaboration to translate investment workflows into practical solutions, leveraging LLMs, RAG and AI agents to boost decision making and research efficiency.

Qualifications

• Strong Python development skills with proven AI/LLM deployment experience.
• Hands-on experience with LLM APIs, RAG, AI agents, and related frameworks.
• Experience delivering AI apps from concept to deployment with real-world impact.
• Good problem-solving skills and ability to translate business needs into technical solutions.
• Excellent communication with investment professionals and stakeholders.
• Experience in hedge funds or asset management is a plus but not required.

Responsabilités

• Partner with portfolio managers and researchers to identify AI opportunities.
• Design, build and deploy AI-powered applications and automated workflows end-to-end.
• Leverage LLMs, RAG, and AI agents to develop investment research tools.
• Work with structured and unstructured financial data, including alternative data and filings.
• Evaluate applications for accuracy, reliability, and effectiveness with user feedback.
• Own solutions and ensure integration into daily investment workflows.

Connaissances

Python

LLM APIs

RAG

AI agents

Concept to deploy

Stakeholder comms

Description du poste

JW Michaels & Co. in San Francisco seeks an experienced AI professional to work directly with portfolio managers and research analysts.

You will own the development and deployment of AI-powered tools that enhance investment research. The role combines hands-on coding with close collaboration to translate investment workflows into practical solutions, leveraging LLMs, RAG and AI agents to boost decision making and research efficiency.