I want to turn my Alpaca account into a fully-automated day-trading machine. The core aim is simple: the bot needs to watch live market data, decide on intraday entries and exits, and execute orders through the Alpaca API with no manual intervention. Key points to keep in mind • Primary function: automated trading only; no customer support or social media extras. • Strategy focus: day trading. The bot should open and close positions within the same session, respect configurable risk parameters, and support rapid position sizing, stop-loss, and take-profit logic. • Exchange connectivity: everything will run on Alpaca for now, but clean modular code will let me extend to Binance, Coinbase, Kraken, or any other REST/WebSocket venue later. I prefer Python, leveraging libraries such as pandas, NumPy, TA-Lib, backtrader (or similar) for strategy logic and backtesting, plus WebSocket streams for real-time ticks. If you can propose a more robust stack that still keeps hosting simple—FastAPI for a lightweight dashboard, Docker for deployment—that’s welcome. Deliverables • Well-structured, documented source code (Git-friendly). • Config file where I can toggle symbols, timeframes, risk limits, and technical indicators. • Backtest report against at least three months of intraday data showing PnL, max drawdown, and Sharpe ratio. • Readme with setup instructions, environment list, and clear guidance on how to switch from paper to live trading. • Brief hand-off call or video walkthrough once everything is ready. Acceptance criteria: after deployment to my Alpaca paper account, the bot must run for one full session without crashing, correctly place, modify, and close orders per the configured rules, and generate a simple end-of-day trade log. If you’ve built algo systems before and can combine solid trading logic with clean, production-ready code, let’s talk.