Development of an Advanced Python-Based HFT Infrastructure Guide

I am looking for a technical collaborator to refine and finalize a high-level publication regarding High-Frequency Trading (HFT) systems developed in Python. The goal is to produce a production-quality open-source repository and a comprehensive technical guide.
The scope includes:
Low-Latency Architecture: Optimizing Python code for execution speed using libraries like NumPy, Pandas, and Asyncio for concurrent data handling.
REST & WebSocket Integration: Detailed examples of robust authentication, order routing, and real-time market data streaming from global exchanges.
Risk Management Frameworks: Implementation of automated stop-loss, take-profit, and rate-limit handling to ensure system stability.
Backtesting Engine: Developing a module for testing strategies against historical tick data with slippage and fee considerations.
Requirements:
Deep understanding of Python 3.10+ and financial market structures.
Experience with API integrations (Binance, Alpaca, or similar).
Ability to write clean, PEP-8 compliant code and technical documentation.