Python · NLTK · spaCy
ABOUT THE ROLE
Join the applied AI team at a fintech company building agent-powered tools for financial advisors. You will own the agent platform, creating reliable systems that help advisors and clients handle complex tasks and collaborate effectively.
WHAT YOU'LL DO
- Build a general-purpose agent that plans and completes multi-step tasks using code execution, web search, and retrieval.
- Develop ambient agents to triage email, process meetings, draft communications, and surface timely follow-up.
- Design the agent harness that coordinates language models, context, tools, retrieval, and business logic.
- Create generative interfaces and human-in-the-loop workflows that support collaboration between advisors and agents.
- Build evaluation infrastructure for both factual financial tasks and judgment-intensive work.
- Develop memory systems that retrieve relevant client context and adapt to advisor preferences over time.
WHAT WE'RE LOOKING FOR
- Four to ten years of full-stack or backend software engineering experience, including building LLM-powered agent systems.
- Production experience building AI agents with orchestration, tool use, and retrieval, and a track record of maintaining high-quality outputs.
- Experience with LLM frameworks, RAG, prompt engineering, APIs, data modeling, and system design.
- Familiarity with Python, TypeScript, React, vector databases, and agent frameworks.
- Experience shipping evaluation infrastructure for non-deterministic AI systems; generative UI or human-in-the-loop interface experience is a plus.
- Strong sof