Skip to content
View soominmyung's full-sized avatar

Block or report soominmyung

Block user

Prevent this user from interacting with your repositories and sending you notifications. Learn more about blocking users.

You must be logged in to block users.

Maximum 250 characters. Please don't include any personal information such as legal names or email addresses. Markdown supported. This note will be visible to only you.
Report abuse

Contact GitHub support about this user’s behavior. Learn more about reporting abuse.

Report abuse
soominmyung/README.md

👋 Hi, I’m Soomin. Welcome to my GitHub!

Personal website: https://soominmyung.com

⚡️ Full-Stack AI Engineer architecting cloud-native agentic workflows and scalable data systems.


🚀 Core Expertise & Solutions

🤖 Agentic AI & LLMOps

  • Multi-Agent Workflows: Designing self-correcting, state-based LLM orchestration using LangGraph to automate complex reasoning and operational tasks.
  • LLM Observability: Integrating LangSmith for full telemetry tracing, evaluating AI outputs, and mitigating hallucination risks in production.
  • Production-Grade RAG: Implementing high-precision retrieval using ChromaDB with advanced metadata filtering and automated vector ingestion.

☁️ Cloud-Native & Deployment

  • Serverless Architecture: Deploying high-performance containerized microservices to GCP Cloud Run using Docker.
  • CI/CD Automation: Building robust deployment pipelines via GitHub Actions for zero-downtime updates and reliable continuous integration.

💻 Full-Stack AI Engineering

  • High-Performance APIs: Building asynchronous backends with FastAPI featuring Server-Sent Events (SSE) for real-time progress streaming.
  • Frontend Integration: Seamlessly connecting AI backends to modern UI platforms using React and TypeScript.

📊 Big Data & ML Engineering

  • Data Pipelines: Engineering ETL/ELT pipelines for massive-scale historical records (41M+ rows) using PySpark and Parquet.
  • Forecasting & Analytics: Translating complex business logic into predictive inventory and anomaly detection models.

🛠 Core Tech Stack

🧠 AI & Orchestration

  • Frameworks: LangGraph · LangChain · MCP (Model Context Protocol)
  • LLMOps: LangSmith · Guardrailed Prompting · AI Output Evaluation
  • Vector DB: ChromaDB · FAISS

⚙️ Backend & Cloud Infrastructure

  • Languages: Python · TypeScript · SQL
  • Backend: FastAPI · Asynchronous Programming · SSE
  • Cloud & DevOps: GCP (Cloud Run, BigQuery) · Docker · GitHub Actions (CI/CD)

📈 Data Engineering & Machine Learning

  • Big Data: PySpark · Parquet · SQL Server (T-SQL)
  • ML Modeling: PyTorch · Transformers · Time-series Forecasting (ARIMA/Prophet)
  • Frontend: React · Framer Custom Code Components

Pinned Loading

  1. purchasing-automation purchasing-automation Public

    Purchasing Workflow Automation

    Python 1 1