I’m building a complete AI-driven platform that trades listed options for me end-to-end. The engine has to recognise and act on the full range of strategies I use—straight buying or selling of calls and puts, multi-leg spreads, straddles, strangles, and any automatic strategy the model itself flags as favourable. Core capabilities I need • Real-time market analysis that fuses live quotes with historical time-series data, news feeds, social-media sentiment and technical indicators such as Wave Trend, VWAP and similar momentum tools. • Automated trade execution through a broker API, with order staging, smart routing and position monitoring. • Built-in risk management covering position sizing, max-loss cut-offs, volatility shocks and margin checks before any order is sent. High-level flow The system should collect and cleanse data, run predictive models, select the best option structure, calculate risk/reward, then place and manage the order without manual intervention. A dashboard that shows open positions, P&L, model confidence and key risk metrics in real time will let me supervise and intervene when required. Deliverables 1. Fully operational trading bot (source code + compiled executable) connected to a paper-trading account for initial validation. 2. Configurable strategy module where I can toggle buying/selling, spreads, straddles, strangles or allow the AI to pick. 3. Risk-management layer with editable limits and alerting. 4. Back-tester that replays historical and simulated live data to prove edge and drawdown parameters. 5. Brief documentation explaining install, config variables, model logic and how to port to a live brokerage account. Acceptance criteria • Latency from data receipt to order placement ≤ 250 ms on my VPS. • Back-test must show at least 500 trades with Sharpe > 1 after fees/slippage on the last two years of SPX options data. • All trades adhere to pre-set max loss and margin rules; violations trigger an alert and auto-shutdown. I’m flexible on tech stack, though Python with libraries like pandas, scikit-learn, TensorFlow and a broker API (IBKR, Tradier, Zerodha, etc.) fits my current environment. Propose your preferred tools if they achieve the same outcome. If you have proven experience building AI or quant systems for options, let’s discuss how you would architect this and timelines for milestones up to live deployment.