AI Applications Engineer

Hedge Fund; New York (NY); On-site; USD 180,000 - 280,000; Full time

Job summary

Hedge Fund in New York seeks a Senior AI Applications / Full Stack Engineer to design and ship end-to-end AI enablement applications for the firm, covering search, retrieval, and agentic tools over internal data and large document corpuses.

The role requires building AI-enabled systems, working with unstructured text, and implementing scalable architectures that orchestrate complex workflows. You will collaborate across teams to deploy production-grade solutions with measurable impact.

Qualifications

• Building end-to-end AI enablement applications.
• Working with unstructured data and large document corpuses.
• Building agentic applications.
• Building search applications with embedding models and RAG.

Responsibilities

• Design and ship full-stack AI applications from data ingestion through UI.
• Build search and retrieval systems using embedding models and RAG over unstructured data.
• Build agentic applications that orchestrate tools and multi-step workflows.
• Work with large, messy document corpuses: parsing, chunking, indexing, evaluation.

Skills

AI/ML engineering

Full-stack development

Search & retrieval

RAG & embeddings

Tools

Python

React

Node.js

PostgreSQL

Job description

Multi-Strategy / Multi-Manager hedge fund with >$3BB in AUM and a core focus on long / short equity strategies is seeking to hire a Senior AI Applications / Full Stack Engineer to build end-to-end AI enablement applications for the firm — search, retrieval, and agentic tools over internal data and large document corpuses.

Responsibilities

• Design and ship full-stack AI applications from data ingestion through UI.
• Build search and retrieval systems using embedding models and RAG over unstructured data.
• Build agentic applications that orchestrate tools and multi-step workflows.
• Work with large, messy document corpuses: parsing, chunking, indexing, evaluation.

Required Experience

• Building end-to-end AI enablement applications.
• Working with unstructured data and large document corpuses.
• Building agentic applications.
• Building search applications with embedding models and RAG.

Nice to have

• Information retrieval background.
• Signal processing background.