Python Algorithmic Trading Developer – Automated Trading System + Broker API

Cozad Quant – Python Automated Trading System + Broker API I am seeking an experienced Python/algorithmic-trading developer to build a complete, independently runnable automated trading system based on an already-defined trading and risk-management architecture. This is NOT a request to invent a trading strategy. The core strategy behavior, position-management logic, and risk architecture are already defined. The project is to implement those specifications into a reliable Python application connected to a broker API. IMPORTANT: The finished deliverable must support both PAPER and LIVE automated execution. Paper trading is the validation/testing stage; live execution capability must already be included in the delivered system. Live capability is not a separate future phase or additional contract. Core trading behavior Opportunity-driven trading No required number of trades per day. The system trades only when defined qualifying conditions are present. If no qualifying opportunity exists, it takes no trade. Signal quality / entry logic Qualifying setups receive a configurable quality/strength score. Initial risk/position size can vary based on setup quality within configurable limits. All signals should be logged, including qualifying and rejected opportunities where practical. Dynamic position sizing Position sizing scales with current account equity. Risk parameters and maximum exposure must be configurable. Position sizing must respect account-level and daily risk limits. Pyramiding / adding to winners The system may add to an existing profitable position when fresh continuation criteria are met. It should not automatically average down into losing positions. Adds must remain within configurable risk/exposure limits. Protected/freed risk from profitable positions may create capacity for additional adds when the defined rules permit. Profit management Support configurable partial profit-taking and runner positions. Support progressive stop ratcheting/trailing/structure-based protection. Profit protection should increase as a trade progresses according to defined rules. Hard daily risk control Configurable maximum daily loss budget. Once the daily loss threshold is reached, new entries must stop for that trading day. Daily profit-floor / equity-ratchet logic As daily realized/unrealized P&L reaches configurable milestones, the system establishes a minimum protected daily-profit floor. That protected floor may ratchet upward as profits increase. The protected floor must never move backward. Valid trading may continue after strong profits as long as qualifying setups remain and the protected daily floor/giveback rules have not been violated. The system should not automatically stop trading merely because a fixed profit target was reached. Execution / broker integration The finished application must: Connect to one agreed broker API for the initial implementation. Retrieve the market/account/order/position information required by the strategy. Submit, modify and cancel orders as required. Track fills and current positions. Support both PAPER and LIVE execution modes. Prevent accidental duplicate orders. Handle rejected orders, API errors, disconnects, stale/missing data and other execution failures safely. Fail safely rather than blindly submitting orders when required state/data is uncertain. Clearly separate paper and live modes so live execution cannot be enabled accidentally. Broker/API selection can be finalized with the selected developer based on API suitability and the instruments being traded. Please state which broker APIs you have personally integrated before. Configuration Important strategy/risk parameters should be configurable rather than buried throughout the source code. Examples include: Risk tiers Maximum position/account exposure Daily maximum loss Profit-floor milestones Giveback limits Pyramiding/add limits Partial-profit settings Stop/trailing parameters Trading/session parameters Paper/live mode The objective is for parameters to be adjustable later without rebuilding the application. Logging / auditability The system should maintain useful logs showing: Signals/setups Quality scores Entries Rejected/skipped entries and reason where practical Position-size calculations Adds/pyramids Partial exits Stops/exits Daily risk status Profit-floor changes Broker/API errors Order rejections Relevant system decisions/actions I should be able to understand afterward what the system did and why. Existing frameworks are welcome Developers who already have reliable reusable Python trading infrastructure are encouraged to apply. I am specifically interested in someone who does not need to reinvent standard broker connectivity/order-management infrastructure from scratch. Existing reusable frameworks/components are acceptable provided: Their use and licensing are clearly disclosed. The delivered application can be independently operated and maintained after handoff. There is no required dependency on developer-controlled servers, accounts or subscriptions. I receive the necessary permanent rights to use and modify the delivered system. Cozad-specific strategy/configuration/code created for this project is included in the handoff. Deliverables Complete working Python automated trading application Agreed broker API integration Paper execution mode Live execution capability Full agreed trading/risk/position-management logic Configurable parameters Execution and decision logging Safety/error handling Testing of core logic and failure states Source code/project files Dependency/setup information Clear setup and operating documentation Clean handoff The application must be independently runnable after handoff without continued developer involvement. Definition of finished This contract is for the complete system described above, not a proof of concept or paper-only prototype. Paper mode will be used to validate the system before live capital is enabled, but live broker execution capability must already exist in the delivered application. Future work would be for genuinely new features, additional brokers/instruments, major strategy additions or other expansion — not completion of functionality included in this scope. Budget $250 fixed price This budget is intentionally targeted toward an experienced developer who already has reusable trading/broker infrastructure and can efficiently implement an already-defined architecture rather than developing an entire trading platform from zero. Please include in your proposal One automated trading system you personally built and which broker/API it used. Which parts of your existing trading infrastructure/framework could be reused for this project. Which broker/API you recommend for this implementation and why. Confirmation that both paper and live automated execution are included in your fixed-price proposal. Your expected turnaround. Any recurring software/data/infrastructure costs required after handoff. Confirmation that the completed system can run independently without developer-controlled infrastructure. Please do not apply solely to design or sell a trading strategy. I am specifically hiring for Python/API implementation of an already-defined automated trading architecture.