Enhance Python NIFTY Trading Automation System

Hi,
We have an existing Python-based NIFTY options automation system running on AWS EC2. The system takes NIFTY spot-based signals from a TradingView-replica swing-zone strategy and executes weekly NIFTY CE/PE option trades through Dhan broker APIs.
The strategy engine, live signal runner, paper/live executor, Dhan order placement, FastAPI backend, and control-center app are already built. The system has also been live-tested.
We are not looking for someone to create a strategy from scratch. The main requirement is to stabilize the production execution architecture.
The current blockers are:
Slow exit execution after SL/TP/TSL conditions.
Broker reconciliation failure where Dhan shows position exited/flat but local runtime still shows open position.
Stale open_positions.csv and pending exit state.
Backend/app status mismatch.
Need to ensure lot size and mode come only from backend/mobile app control.
Need to cleanly separate or document paper/live report paths.
Need live-readiness checklist and robust logs.
The code is hosted on AWS under:
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/home/ubuntu/nifty_automation
Main services:
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nifty-backend.service
nifty-signals.service
nifty-executor.service
Main files include:
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run_live_signals.py
backtest/live_candle_runner.py
backtest/live_signal_adapter.py
execution/live_executor.py
engine/execution/live_executor.py
engine/execution/trade_manager.py
backend/
control-center/
We need a freelancer who can audit the existing system, fix broker reconciliation, reduce exit latency, stabilize backend/app status, and prepare the system for safe daily live trading.
Please do not rewrite the strategy first. The first priority is execution reliability.