Backend Engineer – Algo Trading & AI Bots

0 years

0 Lacs

Posted:1 day ago| Platform: Linkedin logo

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Work Mode

On-site

Job Type

Full Time

Job Description

Role Overview:


We are looking for a Backend Expert on site role (New Delhi/Faridabad) with a strong foundation in algorithmic trading, quantitative finance, and trading bot development. You will work closely with our quant researchers, traders, and AI engineers to design, build, and deploy scalable, real-time trading systems across various platforms including MetaTrader (MQL5), TradingView (Pine Script), and other broker APIs.


Key Responsibilities:


  • Design and develop robust backend systems for real-time trading execution and data processing
  • Build and maintain custom trading bots using AI/ML and deep learning models
  • Integrate with broker APIs (e.g., MetaTrader 5, Binance, Interactive Brokers)
  • Implement strategies in MQL5, Pine Script, and other scripting tools
  • Optimize systems for low-latency execution and high-frequency trading (HFT) environments
  • Collaborate with quant team to backtest, validate, and deploy proprietary strategies
  • Handle large-scale data ingestion, time-series analysis, and signal generation
  • Maintain system reliability, logs, alerts, and risk controls for 24/7 trading


Must-Have Skills:


  • Strong backend development experience (Python, Node.js, Golang,Rust or similar)
  • Hands-on experience with MQL5 and Pine Script (TradingView)
  • Deep understanding of algorithmic trading and quantitative strategies
  • Experience building AI/ML-based trading systems using frameworks like TensorFlow, PyTorch, or Scikit-learn
  • Familiarity with broker APIs, FIX/REST/WebSocket protocols
  • Solid understanding of trading indicators, technical analysis, and market microstructure
  • Experience with backtesting frameworks and financial datasets


Good to Have:


  • Knowledge of Reinforcement Learning or Deep Q-Learning applied to trading
  • Experience with cloud platforms (AWS/GCP), Docker, and CI/CD pipelines
  • Exposure to time-series forecasting and feature engineering for financial data
  • Background in mathematics, statistics, or financial engineering

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