Justin Zhao
I build LLM systems, agentic workflows, and AI products for real users and operational settings.
I design and run production LLM systems with vLLM and llama.cpp for deployment, Kubernetes for load balancing, LoRA and GRPO for fine-tuning, and LangGraph and custom frameworks for orchestration. My work spans no-code LLM pipelines, agentic trading tools, and consumer AI products that have handled hundreds of millions of interactions.
Timeline
From a price monitor script in 2019 to production LLM systems and AI products today, each phase added engineering depth, product experience, and operational rigor.
Democratizing LLM Development: NoCode Platform
Architected a production NoCode LLM application using React Flow for visual orchestration and a FastAPI/Celery backend for asynchronous multi-agent execution across multiple OpenRouter endpoints. Users build complex LLM pipelines through drag-and-drop, reducing weeks of onboarding to minutes of configuration.
Price Monitor 2.0: Agentic Trading System
Built an agentic trading framework where agents fetch live market data, build context autonomously, generate decisions, and review each other's outputs before acting. Customizable orchestration layers bring context-aware, auditable trading to non-technical users without engineering overhead.
M.S. Computer Science
University of Colorado Boulder training in machine learning and cloud computing, applied to the systems and products built above.
Data Analyst, ByteDance
Applied analytical rigor to advertising strategy across multiple product lines, consistently driving traffic growth through data-informed decisions. Brought an automation mindset to reporting and campaign analytics, shifting the team from manual data collection to strategic work.
Builder Journey: AI Products and Ventures
Started building AI products in 2019 and has continued since. As founding engineer at Prompter Store LLC, shipped three concurrent consumer products from ideation to production: a multi-modal AI chat platform that scaled to hundreds of millions of user interactions, an AI tools directory, and a consumer network product.
Where It Began: Price Monitor, 2019
Built the first iteration of Price Monitor in 2019, a rule-based system for tracking prices and surfacing actionable signals. The same core problem that drove the 2019 version, making market information legible and actionable without constant manual monitoring, is what the 2026 agentic system solves at a fundamentally different level of autonomy.