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3+ years of experience
Full Stack Engineer building scalable SaaS platforms. Expert in Next.js, React, TypeScript and Node.js, NestJS, PostgreSQL, architecting systems serving 1.2B+ devices. Leverage generative AI (Copilot, Claude, OpenAI) daily. Founded Masst.dev, a developer toolkit featuring CLI scaffolding, UI components, and AI-powered system design resources. Skilled in microservices, multi-tenant systems, and leading teams of 4+ developers. SKILLS Languages: TypeScript, JavaScript, Go, Python, SQL, HTML, CSS Frontend: React.js, Next.js, Tailwind CSS, ShadCN, Zustand, React Query, Redux Backend: Node.js, NestJS, Express.js, FastAPI, REST APIs, GraphQL, WebSockets, Microservices, RabbitMQ Databases: PostgreSQL, MongoDB, Redis, Prisma ORM, Supabase, TimescaleDB Cloud & DevOps: AWS (EC2, S3, Lambda, RDS), Docker, Kubernetes, Vercel, GitHub Actions, Jenkins, CI/CD AI & Tools: LangChain, Pinecone, OpenAI APIs, GitHub Copilot, Claude AI, Git, Jest, Cypress, Jira, Figma

MasstTrader is a full-stack AI-powered trading education and strategy platform built to bridge the gap between trading ideas and execution. Users connect their MetaTrader 5 broker account and describe trading strategies in plain English — the AI parses natural language into structured, executable rules with precise entry/exit conditions, stop losses, and take profits. The platform backtests these strategies against real historical market data, presenting results through interactive TradingView candlestick charts with trade markers, equity curves, win/loss breakdowns, and per-trade P/L analysis. An AI explainer then reviews backtest performance, identifying when the strategy works, when it fails, and how to improve it. For live trading, MasstTrader streams real-time prices, positions, and technical indicators over WebSocket, with a built-in algo trading engine that automatically executes trades based on strategy rules while monitoring conditions in real time. The AI Trade Analyzer lets users submit actual trades they took and receive an alignment score against their strategy, along with detailed coaching feedback. An AI Tutor module delivers personalized trading lessons adapted to the user's experience level and preferred instruments, with interactive follow-up chat. The platform supports light and dark themes, persistent strategy storage in SQLite, and a searchable symbol picker covering Forex, Metals, Crypto, and Indices. Built with Next.js 16, FastAPI, Groq's Llama 3.3 70B, and deployed on Vercel + AWS EC2.
7 Feb 2026