Built core technology infrastructure for AI Systemics — an AI company developing intelligent solutions that bring institutional-grade capabilities to everyday users. Primary focus on their flagship product, Quanntick™, an AI-powered algorithmic trading platform that brings institutional-level trading to individual investors. Developed the machine learning pipeline powering real-time market analysis and signal generation — processing live CME Group licensed market data, running predictive models, and executing automated trading strategies on futures markets with precision and speed. Built the performance tracking dashboard giving users transparent visibility into trade execution, strategy performance, and portfolio metrics in real-time. Engineered the full stack: Python backend for ML model serving and trade execution logic, real-time data ingestion pipelines processing high-frequency market feeds, React frontend for the trading dashboard with live charts and performance analytics, and cloud infrastructure designed for low-latency execution where milliseconds matter. Implemented automated systems running 24/7 with reliability patterns — failover handling, execution safeguards, and monitoring that ensures trades execute correctly even during volatile market conditions. The platform democratizes access to quantitative trading strategies previously available only to hedge funds and institutional desks — making advanced AI-driven trading accessible to individual investors. Tech: Python, Machine Learning, React, TypeScript, Real-Time Data Processing, Cloud Infrastructure, API Integration, Redis, PostgreSQL