Applied AI Engineer

This Jobot Job is hosted by: Jon Lopez
Are you a fit? Easy Apply now by clicking the "Apply Now" button and sending us your resume.
Salary: $150,000 - $250,000 per year

A bit about us:

Applied AI Engineer
Full-time | Hybrid (New York, NY - Bryant Park)
In-person 4 days per week (Wednesdays remote)

Role Overview
We are seeking software engineers to chart the course of how AI reshapes institutional finance. In this role, you will build AI Infrastructure-including observability, agent orchestration, and data orchestration-leveraged by some of the world's most sophisticated hedge funds. You will work at the intersection of AI implementation and financial software, turning complex investment workflows into elegant, production-grade applications.

Speed is fundamental to our DNA; we deliver fully customized platforms in weeks, requiring you to ship with conviction and iterate based on real-time feedback from investment teams

_source=Dice

Why join us?

About the Platform
We build the ecosystem that makes hedge funds AI-native. By connecting proprietary data and encoding investment expertise into specialized agents, we automate the highest-value workflows for global asset managers. Unlike standard AI startups, our growth is driven by direct client value and a team with deep roots in the world's most successful investment firms.

Job Details

Key Responsibilities
AI-Powered Feature Development: Build LLM-driven research intelligence, natural language query layers, and agentic workflows that compress weeks of analyst work into seconds.

Agentic Tooling & MCP Integration: Design and implement MCP-connected data sources and AI orchestration layers using frameworks like LangGraph and similar tools.

Full-Stack Engineering: Build end-to-end applications for portfolio analytics and risk management, from high-performance Python backend APIs (FastAPI) to responsive React frontends.

Data & Analytics: Develop ETL pipelines for critical market data and implement analytics layers for performance/risk calculations using Pandas and Polars.

Infrastructure: Work fluidly with Kubernetes within client environments to ensure fast, reliable deployments.

Qualifications
Experience: 3-8 years as a Full-Stack SWE or Applied AI Engineer.

Domain Expertise: Previous experience within institutional investment or Fintech environments is required.

Technical Proficiency: Fluent in modern AI tooling, Python, React, SQL, and Azure.

Mindset: Deeply curious about how asset managers operate and capable of delivering high-quality software on compressed timelines.

Logistics & Team

Company Profile: We are a cash-flow positive, client-funded organization that has bootstrapped to $10M+ ARR.

The Team: A lean, elite group of approximately 25 employees. Our team combines engineers from top-tier financial institutions (including "Tiger Cubs" and major multi-strategy funds) and leading AI startups. We bridge the gap between deep finance domain knowledge and cutting-edge AI engineering.

Interested in hearing more? Easy Apply now by clicking the "Apply Now" button.

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