- KelAI
- New York, NY
- Full-Time
- 77 days ago
- $130,000 – $215,000
Applied AI Engineer.
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Applied AI Engineer: our view in 3 lines...
- The Role:This role is for an engineer building applied AI systems for investment research and alpha discovery in a venture-backed company serving hedge funds and institutional investors.
- The Person:The person will build agentic workflows, run AI agent evaluations, deploy AI systems into production, improve agent performance, and work with quant researchers and infrastructure engineers.
- Requirements:The ideal candidate has 2-3 years of experience, strong software engineering skills, hands-on experience with LLMs, agents, evaluations, RAG, tool-calling, or AI workflow orchestration, and a Master’s degree in a related technical field.
About the role
What You’ll Do
- Build agentic workflows for investment research, data analysis, and alpha discovery
- Design and run evaluations for AI agents, including reliability, reasoning quality, and task-completion benchmarks
- Deploy AI systems into production workflows used by internal teams and institutional investors
- Improve agent performance through prompt design, tool use, retrieval, memory, orchestration, and feedback loops
- Work closely with quant researchers and infrastructure engineers to turn research workflows into robust AI-powered systems
What We’re Looking For
- 2-3 years of experience in a tech startup, AI lab, or big tech environment
- Strong software engineering skills and experience shipping production AI systems
- Hands-on experience with LLMs, agents, evaluations, RAG, tool-calling, or AI workflow orchestration
- Master’s degree in computer science, AI, machine learning, engineering, or a related technical field
- Strong ownership mindset and ability to operate in a fast-moving early-stage environment
Founded by a former WorldQuant portfolio manager and Head of Event-Driven Systematic Strategies, KelAI is a YC-backed, venture-funded company building the autonomous alpha engine for hedge funds, traders, and institutional investors.
We help investment teams turn data, research, and market ideas into agentic quant workflows for signal generation, thesis monitoring, and better investment decisions.
