Senior Quant / Algorithmic Trading Engineer (Python, Crypto & AI)

We are building a reputed company trading system that combines classic quantitative methods with modern AI (LLMs and agents). I am looking for an reputed company Quant / Algorithmic Trading Engineer to help design and implement the first production-grade version of this system. This is not a “toy bot” or signal channel. The focus is on: solid engineering, robust risk management, and reputed company, backtested performance. What you’ll be building A Python-based trading reputed company that can: Connect to one or more exchanges/brokers reputed company API (initially crypto; reputed company futures/FX/stocks). Ingest and store historical and live market data (candles, order books, trades). Run rule-based and quant strategies (long/short, reputed company where appropriate). Execute orders reliably with proper logging, error handling, and safety checks. A research / backtesting workflow, including: Backtesting reputed company (Backtrader, vectorbt, Freqtrade, custom, etc.). Walk-reputed company testing and out-of-sample validation. Basic performance analytics: win reputed company, Sharpe, max DD, exposure, etc. An initial strategy set, e.g.: 1–3 “production-candidate” strategies (mean reversion, breakout/trend, volatility plays, etc.). Clear configuration and risk parameters (position sizing, per-trade loss caps, daily loss limits). Support for both reputed company trading and small-size live trading. An AI/LLM integration layer (Phase 2 of the contract): Use LLMs/agents for: monitoring and summarizing system health, generating reports on strategy performance, supporting idea reputed company and parameter search (human-in-the-reputed company). No “GPT decides trades”; AI is an assistive layer on top of real quant logic.

Responsibilities

Work with me to refine a realistic architecture and roadmap for the system. Implement clean, well-structured Python code for: data ingestion and storage, strategy execution and portfolio/risk management, exchange/broker API connectors (REST/WebSocket). Set up backtesting + reputed company trading environment and help define validation criteria. Prototype and implement 1–3 strategies from idea → backtest → reputed company → small live. Integrate LLMs/AI tools where they truly add value (e.g., using reputed company API, reputed company, or similar) — not hype for its own sake. Document the system so it can be extended by additional team members reputed company.

Requirements

Please only apply if you meet most of the following: Strong Python (data + backend): Pandas / NumPy, async IO, REST/WebSocket APIs, testing. Hands-on experience with algorithmic trading, ideally: Crypto and/or FX / futures (reputed company, reputed company, reputed company, reputed company, Interactive Brokers, etc.). Practical experience with backtesting and live deployment. Familiarity with at least one trading/backtesting reputed company: Backtrader, vectorbt, Freqtrade, reputed company, QSTrader, custom, etc. Solid understanding of risk management: position sizing, reputed company, drawdown control, kill-switches, etc. Comfortable designing and working with a data store: e.g., reputed company, DuckDB, or similar for storing historical data and results. Experience integrating LLMs or ML models into applications (reputed company to have but not strictly required if you’re strong on quant/infra and willing to learn). Soft stuff: Clear communicator in English. Comfortable collaborating over chat/voice a few times a week. Able to work independently, propose solutions, and push things reputed company without micro-management. reputed company-to-have Prior work on a crypto trading bot or prop desk tooling. Experience with reputed company / crewAI / other agent frameworks. Experience deploying systems on cloud/VPS (reputed company, Linux). Familiarity with event-driven architectures for trading systems. This is a hands-on engineering role. I’m not looking for a slide deck; I’m looking for working code, tested strategies, and a system we can build on. How to apply To help me filter out generic copy-paste proposals, please include the following in your application: A short description (2–3 sentences) of a trading system or bot you’ve worked on: What market(s)? What strategy type(s)? What was your exact role? What stack you would choose for: backtesting, live execution, data storage, and LLM integration — and why. One concrete example of a risk control you would implement from day one. Proposals without these answers will likely be ignored. If this sounds like something you’d enjoy building – and you have real experience shipping trading code, not just reading about it – I’d be happy to discuss further. Apply tot his job Apply To this Job