Zerodha API Algo Trading Automation

I need an experienced developer to deploy my options-selling trading strategy on Zerodha Kite Connect (Python). IMPORTANT: The strategy is already fully designed, documented, and the core logic is written in Python and unit-tested. This is mostly INTEGRATION + TESTING + DEPLOYMENT, not strategy design. WHAT'S ALREADY READY (I will share): - Complete strategy specification document (every rule, formula, edge case defined) - Core strategy engine in Python (tested, acceptance tests pass) - Indicators (SMA, ATR, ADX), backtest skeleton, and a live-bot skeleton WHAT I NEED YOU TO DO: 1. Review my existing Python strategy code against the spec 2. Integrate with Zerodha Kite Connect API (live 5-min option data + order placement) 3. Implement multi-leg basket orders (a hedge BUY first, then the main SELL) for margin reduction 4. Robust order management: order tracking, fill detection, partial fills, rejections, API timeouts, cancel-after-3-candles, and auto square-off at end of day 5. Multi-instrument scanning (~24 option strikes for NIFTY + SENSEX, both CE & PE, simultaneously) 6. Build a backtest using Kite historical data and validate against my 3 months of real trade journal (the bot must TAKE my winning setups and SKIP the rule-violation ones) 7. Help me run it in paper / DRY-RUN mode first, then deploy live MUST HAVE: - 3+ live Zerodha Kite Connect bots built before (please share examples) - Strong Python + options trading + multi-leg order experience - India-based preferred (timezone + API access) - Willing to work milestone-based PLEASE ANSWER IN YOUR BID: 1. How many live Kite Connect bots have you deployed? 2. How do you handle order rejections, partial fills, and API timeouts? 3. Do you have experience with multi-leg / basket (hedge) orders? 4. Your time + cost estimate? Note: I will provide API keys myself on my own machine - please do not ask me to share keys. I will share the full spec + code with shortlisted developers. Since the logic is done, I'm looking for a clean, safe, well-tested deployment.

Project ID: 40480405