You will bridge the gap between our financial data and our users - building intuitive React interfaces, robust Python backends, and Retrieval-Augmented Generation (RAG) pipelines that turn complex proprietary data into actionable insight for our analysts and traders.
This is a high-impact role for an engineer who is comfortable owning features end-to-end and who takes pride in building reliable, well-crafted software. We aren't looking for an AI researcher; we need someone who can ship real products around LLMs and make them genuinely useful to the people who depend on them every day.
What You'll Do- Build and maintain scalable internal web applications using Python (FastAPI/Flask) and React, from database architecture through to front-end interfaces
- Implement and optimize RAG systems to extract insights from internal financial documents and proprietary data sources
- Write complex, performant SQL queries to interface with our relational databases, and design and manage Vector Databases for AI retrieval workloads
- Build internal features that accurately handle and display sensitive financial data - positions, P&L, Mark-to-Market valuations - for our analysts and traders
- Work closely with investment, operations, and technology teams to translate business requirements into working, production-quality software
- Support ongoing system improvements, troubleshooting, and optimization of existing applications and pipelines
- Contribute to documentation, testing, and development best practices as our engineering function matures
What We're Looking ForRequired- 3+ years of production experience with Python and modern JavaScript (React)
- Strong SQL skills are an absolute must - comfortable writing and optimizing complex queries against relational databases
- Working knowledge of RAG architectures, LLM APIs, and tooling such as LangChain or LlamaIndex
- Familiarity with financial concepts such as P&L, Mark-to-Market, and Security Master records - or a proven track record of learning complex business domains quickly
- Excellent communication skills; comfortable working with both technical and non-technical stakeholders
- High degree of ownership: able to manage multiple priorities independently and deliver quality results in a fast-paced environment
Nice to Have- Familiarity with C#/.NET for occasional integration with existing internal systems
- Prior experience in financial services, asset management, or a closely related environment
- Experience with Vector Databases (e.g., Pinecone, Weaviate, pgvector) in a production setting
CompensationIn accordance with New York State Pay Transparency Law, the base salary range for this position is $150,000 - $220,000 per year. Base salary does not include additional compensation such as performance-based cash bonuses tied to individual and fund results. Offers are determined by candidate experience and geographic location.
