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Python Algo Trading Bot — Brokerage API + WebSocket + Claude AI Decision Layer (US / NSE / Forex)

Remote, USA Full-time Posted 2026-06-18

I'm building an autonomous AI trading agent that makes decisive investment decisions across US equities, Indian markets (NSE/BSE), and Forex. The bot uses Claude Sonnet 4.6 (Anthropic's API) as its reasoning and decision engine — not as a chatbot, but as a structured market analyst that returns BUY / SELL / HOLD decisions with justification. I am NOT looking for a general AI/LLM developer. I need someone who understands markets AND can build production-grade Python trading infrastructure. ─────────────────────────────────────── WHAT I NEED YOU TO BUILD ─────────────────────────────────────── 1. DUAL TRIGGER ARCHITECTURE - APScheduler (AsyncIOScheduler): market open/close hooks, 15–30 min periodic scans, EOD summary - WebSocket streams (asyncio): event-driven triggers on price move %, volume spikes, stop-loss/take-profit hits - Both running simultaneously in a single asyncio event loop - Per-symbol cooldown timer to rate-limit Claude API calls 2. MULTI-MARKET SESSION MANAGER - NSE/BSE: 11:45 PM – 6:00 AM ET (via Zerodha Kite API or equivalent) - London (LSE): 3:00 AM – 11:30 AM ET - US markets: 9:30 AM – 4:00 PM ET (Alpaca API) - Forex: 24/5 continuous (OANDA or Alpaca Forex) - Weekday-only execution with proper market calendar awareness 3. BROKERAGE EXECUTION LAYER - Alpaca Markets API: US equities + options - Zerodha Kite or Angel Broking API: NSE/BSE - Order types: market, limit, bracket (with built-in stop-loss + take-profit) - Position sizing logic based on portfolio % risk per trade - Max drawdown kill switch — bot pauses if daily loss exceeds threshold 4. REAL-TIME MARKET DATA - Alpaca WebSocket: live bars, quotes, trade events for US - Polygon.io or equivalent: backup data feed - NSE feed via broker API - News/sentiment feed (optional): lightweight RSS or Alpaca news stream 5. RISK MANAGEMENT MODULE - Per-trade risk: configurable % of portfolio (default 1–2%) - Daily loss limit: hard stop at X% drawdown - Max open positions: configurable cap - No pyramiding without explicit Claude confirmation 6. STATE + LOGGING - Redis: live session state, symbol cooldowns, open position cache - SQLite or Postgres: full trade log (entry, exit, P&L, Claude reasoning stored) - Structured JSON logs per session 7. BACKTESTING FRAMEWORK - At minimum: vectorized backtest on 6+ months of historical data - Strategy: momentum + mean-reversion hybrid (I will define the logic, you implement the framework) - Output: Sharpe ratio, max drawdown, win rate, expectancy ─────────────────────────────────────── TECH STACK (NON-NEGOTIABLE) ─────────────────────────────────────── - Python 3.11+ - asyncio + APScheduler (AsyncIOScheduler) - Alpaca-py SDK (WebSocket + REST) - Zerodha Kite Connect (or Angel Broking SmartAPI) for India - Redis (via redis-py) - SQLite or Postgres - Docker (containerized deployment on VPS) - Anthropic Python SDK (claude-sonnet-4-6 model) NO: LangChain, n8n, AutoGen, CrewAI, no-code tools, or MetaTrader. ─────────────────────────────────────── MUST-HAVES (HARD REQUIREMENTS) ─────────────────────────────────────── ✅ You have shipped at least one LIVE algorithmic trading bot connected to a real brokerage (show me) ✅ You understand position sizing, risk-reward ratios, and drawdown management — not just coding ✅ You know asyncio deeply — this is not a synchronous script ✅ Clean, modular, well-commented code — I will maintain and extend this myself ✅ Full code ownership transfers to me — no black boxes, no encrypted modules ✅ You can explain your architecture decisions in plain English ─────────────────────────────────────── NOT WHAT I NEED ─────────────────────────────────────── ✗ ChatGPT / RAG chatbot specialists with no trading background ✗ Anyone whose portfolio is only CRM bots, lead gen, or voice agents ✗ MetaTrader EA developers without Python experience ✗ Anyone proposing LangChain or agent frameworks as the core ✗ Copy-paste bots from GitHub — I need custom architecture ─────────────────────────────────────── TO APPLY ─────────────────────────────────────── Start your proposal with the phrase: DUAL TRIGGER Then answer these three questions: 1. Name one live trading bot you've shipped — what brokerage, what strategy, what language? 2. How would you handle a situation where the WebSocket drops mid-session? 3. What's your approach to preventing the Claude API from being called on every price tick? Proposals that don't answer all three will not be read. Apply tot his job Apply To this Job

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