Delivered

NEURADAO — AI Trading Platform

A live AI trading platform, shipped in 20 days.

Python
AWS

Screenshot of the NEURADAO landing page hero section — Landing hero

Client: NEURADAO
Timeline: Oct 2025
Role: Team Lead, Software Engineer
Outcome: Live in 20 days

About the project

Led three engineers from an empty repository to a live AI trading platform in 20 days (Oct 2025): wrote the trading logic, AI chatbot and automation backend, and deployed on AWS.

The problem

NEURADAO wanted a live AI trading platform, and wanted it fast: an empty repository at the start of October 2025, and a product people could use within weeks. The risk with a deadline like that is a demo that never becomes a working system.

What I built

As Team Lead, Software Engineer on contract, I led three engineers. I set the architecture and the plan, and I wrote the core of the product myself:

The trading logic behind the platform's AI trading agent, which users configure and whose performance they can follow.
An AI chatbot that answers users' trading questions.
The automation backend that runs the platform.
Deployment on AWS.

The product around it includes a landing page, an earnings dashboard showing each user's returns, and a Chrome extension.

How it works

The backend is split by language where it fits: TypeScript for the application services and Python for the trading and AI parts, with PostgreSQL as the shared store. Users set up the AI trading agent, the automation backend runs it, and results flow into the earnings dashboard. The chat assistant sits alongside so users can ask about the platform and their trades in plain language.

Outcome

The platform went from an empty repository to live in 20 days, deployed on AWS: the landing page, the configurable AI trading agent, the chat assistant, the earnings dashboard and the Chrome extension, on top of the trading logic and automation backend I wrote.