AI Engineer - Boutique Hedge Fund Front Office Team
Job Description
About the Role
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This role sits inside the investment team itself, not a separate technology function, building the AI infrastructure and tooling that the fund’s analysts and portfolio managers will use to source, process, and act on information faster. The work touches research workflows directly: if the tooling is slow or unreliable, the investment team’s edge narrows. This is a build-from-scratch mandate at a fund that has decided AI capability is now core to how it invests, not a side project.
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What You’ll Do
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- Design and build AI/ML tools and LLM-based systems that plug directly into the investment team’s research process
- Build and maintain data pipelines feeding models and internal tools
- Prototype rapidly with PMs and analysts, then harden what works into production
- Evaluate and integrate third-party models, APIs, and frameworks where they beat building in-house
- Own the technical roadmap for AI tooling as the function scales
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Must-haves
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- Professional experience in finance (this is non-negotiable for the role)
- Strong Python and experience building production-grade software, not just research notebooks
- Direct experience building with or deploying LLMs or ML models
- Comfort working shoulder-to-shoulder with investment professionals, not behind a ticket queue
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Nice-to-haves
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- Experience with LLM orchestration frameworks (LangChain, LlamaIndex, or custom equivalents)
- Cloud infrastructure experience (AWS, GCP, or Azure)
- Prior exposure to a specific asset class or investment process
- Open-source contributions or published work in applied ML
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