Applied AI Engineer

About the Role

Build AI powered financial software for institutional investment teams, working across AI implementation and full stack product development. You will turn complex research, analytics, and investment workflows into practical applications, shipping quickly and improving them through direct user feedback.

What You'll Do

• Build user facing AI features, including research tools, natural language queries, summarization, and agentic workflows.

• Develop agentic pipelines, MCP connected data sources, and orchestration layers using LLM APIs and relevant frameworks.

• Create client specific applications for portfolio analytics, risk management, and research, from backend APIs to responsive React interfaces.

• Design Python APIs and reliable data pipelines for financial data, analytics, and AI inference.

• Implement performance and risk analytics using time series and linear algebra tools such as Pandas and Polars.

• Deliver working software on compressed timelines, gather feedback from investment users, and iterate on the product.

What We're Looking For

• Three to eight years of experience as an applied AI engineer building agentic AI products.

• Experience taking user facing agentic AI features from initial concept to production, with a strong grasp of the agentic loop and practical AI tooling.

• Strong Python and API development skills, including experience with FastAPI, Flask, or Django, plus React, SQL, and Azure.

• Hands on experience with LLM APIs, MCP servers, agentic frameworks such as LangChain or similar tools, and prompt engineering.

• A track record of solving loosely defined problems in unstructured environments, and interest in how institutional investors make decisions and use technology.

• Experience in institutional investing, fintech, or another data intensive and quantitative field is relevant.

Compensation & Benefits

Annual salary range: $200,000 to $250,000 USD. Visa sponsorship is available.

Location

Hybrid role based in New York, United States.