Python Developer for Real-Time AI Momentum Trading System

We are seeking an experienced developer to build a real-time momentum trading application that connects to brokerage and market-data APIs. The system must process live trade, quote, volume, liquidity, and order-book data to identify rapid price momentum and submit trades when defined conditions are met. It must support: * Historical backtesting * Real-time observation without trading * Paper trading * Live trading with manual activation * WebSocket market-data streaming * Broker API integration * Millisecond-to-minute momentum calculations * Price velocity and acceleration * Trade-rate and volume expansion * Buy/sell pressure and order-book imbalance * Spread, liquidity, and estimated slippage controls * Position, order, and risk management * Automatic reconnecting, logging, and monitoring * Dashboard or control panel The first version should use configurable mathematical rules rather than machine learning. The system should be provider-independent, but initial integrations may include Alpaca, Interactive Brokers, or another market-data provider. Preferred technology includes Python, asyncio, WebSockets, FastAPI, PostgreSQL or TimescaleDB, Redis, Docker, NumPy/Pandas/Polars, and Grafana or a custom dashboard. Applicants should have experience with algorithmic trading, real-time event processing, brokerage APIs, market microstructure, backtesting, and production-grade Python systems. Please provide examples of similar trading or real-time financial applications you have developed.