A New York firm rebuilding wealth management from the ground up with AI.
Member of Technical Staff, Agent Platform
We're building a reasoning layer that sits between language models and capital markets—an agent platform that can internalize financial regulation, client constraints, and real-time market structure, then act with calibrated judgment. The surface problem is personalized portfolio management at scale; underneath, it's a hard systems challenge spanning retrieval, planning, execution, and guardrails. You'll design the architecture that lets agents decompose multi-step financial tasks, retrieve from dense proprietary knowledge stores, and execute safely in high-stakes environments. This is a systems-and-models role where engineering rigor and financial intuition carry equal weight.
What they're looking for
- 4–10 years building production machine learning systems, with deep Python fluency
- Experience designing agent architectures—planning, tool use, memory, and retrieval-augmented generation
- Strong grasp of vector databases and embedding strategies for dense document corpora
- Comfort working across the stack; TypeScript and React experience is a real plus
- Prior exposure to finance, legal, or security domains where correctness and auditability are non-negotiable