Startups · AI

Founding Engineer

Aqua · New York, NY, US · On-site

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About Aqua

The AI-Native Turnkey Alternative Investment Platform (TAIP). Backed by Y Combinator.

About the role

This is not a clean-sheet build. We operate a production platform handling real money for institutional clients. The interesting engineering problems come from that constraint — you have to build fast and get it right, because the cost of getting it wrong is measured in regulatory risk and real dollars.

What they're looking for

  • You've built and shipped systems that handle real money, real data, or real compliance constraints — not just prototypes
  • You treat testing, validation, and edge case handling as part of the work, not a separate phase someone else does
  • You've operated in an environment where you had to figure out the "what" and the "how," not just execute against a spec
  • You're comfortable working across backend systems, data pipelines, and infrastructure — and you can pick up new tools and frameworks fast when the problem demands it
  • You've worked with or built LLM-powered applications and understand both the potential and the failure modes
  • You'd rather own a hard problem at a small company than be a cog in a machine at a big one
More about this role

The alternative investment industry moves trillions of dollars a year through fax machines, PDFs, and manual data entry. A single subscription into a private equity fund can require 40+ pages of documents, hand-keyed across three different systems, touched by five different people, and take weeks to settle. The infrastructure is decades behind public markets — and the entire wealth management industry knows it.

Aqua is fixing this. We're the transaction and automation platform for alternative investments, used by some of the largest RIAs, broker-dealers, and asset managers in the country — including Blackstone, Apollo, Blue Owl, and JLL. We're on track to process $5B in new transactions in 2025. We're a YC-backed company with Series A funding.

This is not a clean-sheet build. We operate a production platform handling real money for institutional clients. The interesting engineering problems come from that constraint — you have to build fast and get it right, because the cost of getting it wrong is measured in regulatory risk and real dollars.

Agentic document systems. We're building LLM-powered pipelines that ingest, classify, extract, and generate complex financial documents —...

Read the full posting on Aqua's site ↗

Engineering

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