← All Positions

Applied AI Engineer

Innovative financial technology firm New York, NY Direct Hire Other

Job Summary

Join a dynamic team building AI infrastructure and applications that power sophisticated investment workflows for institutional clients. You'll develop LLM-driven features, agentic systems, and full-stack platforms that transform complex financial processes into efficient, production-ready tools. This role demands speed, technical depth, and a passion for how AI reshapes institutional finance.

Essential Functions

  • Build LLM-powered features into client platforms, including research intelligence, natural language queries, automated summarization, and agentic workflows
  • Design agentic pipelines and integrations with data sources using modern AI frameworks
  • Develop end-to-end full-stack applications for portfolio analytics, risk management, and research workflows
  • Create high-performance backend APIs using Python frameworks like FastAPI
  • Build responsive frontend interfaces in React for interacting with financial data
  • Develop and maintain ETL pipelines for financial market data including positions, securities, and risk metrics
  • Implement analytics layers using timeseries and linear algebra operations with tools like Pandas or Polars
  • Deploy applications fluidly in Kubernetes environments for fast, reliable delivery

Required Qualifications

  • 3-8 years of experience as a full-stack software engineer or applied AI engineer in institutional investing or fintech
  • Proven track record building user-facing products from 0-to-1 using agentic AI tooling
  • Hands-on experience with LLM APIs, agentic frameworks, and prompt engineering
  • Expertise in Python, including API development with FastAPI, Flask, or Django
  • Understanding of agentic loops in modern AI frameworks
  • Ability to thrive in unstructured environments and solve loosely defined problems
  • Active use of AI tools with conviction that AI transforms software development
  • Deep interest in how institutional investors operate and make decisions

Preferred Qualifications

  • Experience in quantitative fields like biotech or data-intensive environments
  • Familiarity with institutional investor operations from roles at leading firms
  • Track record of shipping software quickly based on user feedback
  • Kubernetes deployment experience in client environments
  • Background in financial analytics or risk management systems

Technical Skills

  • Python (FastAPI, Flask, Django)
  • React for frontend development
  • Agentic AI frameworks (LangGraph, similar tools)
  • LLM APIs and prompt engineering
  • ETL pipelines for financial data
  • Pandas, Polars for timeseries and analytics
  • Kubernetes deployments
  • Backend API design
  • Full-stack application development
  • Data orchestration and observability

Apply for This Position

📄 Drag and drop or browse PDF, DOC, or DOCX (10 MB max)