Artificial Intelligence Engineer (Fintech or Biotech Background)

Job Title: Applied AI Engineers

Job Location: New York (Hybrid – Wed Remote)

Salary: $200k to $250k

Our client, a fast-growing AI fintech startup, is hiring Applied AI Engineers to chart the course of how AI is reshaping institutional finance. You'll build AI infrastructure (observability, agent orchestration, expert skills, tools as CLIs and MCP, data orchestration, and UI component libraries) leveraged by some of the world's most sophisticated hedge funds — working directly with their investment teams to turn complex workflows into elegant, production-grade applications.

This role sits at the intersection of AI implementation and financial software. You won't just use AI tools — you'll build AI-powered features directly into client platforms: LLMdriven research intelligence, agentic workflows, MCP-connected data sources, and automation layers that compress weeks of analyst work into seconds.

The ideal candidate is a strong full-stack engineer who is fluent in modern AI tooling and deeply curious about how hedge funds and asset managers think, invest, and operate. Speed is a core part of the job — the company delivers fully customized platforms in weeks, not months.

What You'll Do

• AI-Powered Feature Development: Build LLM-powered features into clientfacing platforms — research intelligence tools, natural language query layers, automated summarization, and agentic workflows that change how investment teams work.

• Agentic Tooling & MCP Integration: Design and implement MCP-connected data sources, agentic pipelines, and AI orchestration layers using frameworks like Claude Code, LangGraph, OpenClaw, OpenCode, and similar.

• Full-Stack Application Development: Build end-to-end applications tailored to each client's unique portfolio analytics, risk management, and research workflows from backend APIs to responsive frontends.

• Backend Services: Design and maintain high-performance APIs using Python (FastAPI or similar) powering client-specific data access, analytics, and AI inference.

• Frontend Development: Build intuitive, responsive UIs in React enabling investment teams to interact with complex financial data clearly and efficiently.

• Data Pipeline Development: Build and maintain ETL pipelines handling positions, securities, risk metrics, and research signals with reliability and performance.

• Financial Analytics: Implement analytics layers for performance and risk calculations using timeseries and linear algebra operations (Pandas, Polars).

• Ship Fast, Iterate Often: Deliver working software in compressed timelines, gather direct user feedback, and continuously improve — treating speed and quality as complementary.

• Kubernetes Deployments: Work fluidly with Kubernetes within each client environment to ship fast and reliably.

What You Bring Required:

• 3–8 years as a full-stack SWE or applied AI engineer (institutional investor or fintech)

• Demonstrated record using agentic AI tooling effectively (Claude Code, Codex, MCP servers) and building user-facing products 0-to-1

• Strong Python expertise (non-negotiable; API experience with FastAPI, Flask, or Django highly preferred)

• First-principles understanding of the agentic loop used within most agentic frameworks (Codex, Claude Code, OpenCode, Cline, etc.)

• Effective in unstructured environments and ability to solve loosely defined problems

• Genuine conviction that AI is transforming software and deep interest in how institutional investors think and use tech

Preferred:

• Institutional investor or fintech experience (Two Sigma, DE Shaw, Citadel, P72, Addepar) or other data-first/quantitative fields (health/biotech)

• AI implementation experience — hands-on building with LLM APIs, MCP servers, agentic frameworks (Claude Code, OpenClaw, LangChain), prompt engineering, etc.