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  • 03:35 (UTC +09:00)

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hongvincent/README.md

Subin Hong

AI/LLM Engineer focused on production GenAI systems, RAG evaluation, AWS Bedrock delivery, and agent tooling.

Most recent work is private or organization-owned. This profile highlights stack, delivery scope, and public artifacts rather than treating public repos as the full portfolio.

Python TypeScript SQL AWS Bedrock AWS Lambda FastAPI RAG & Evals Observability Playwright pytest GitHub Actions

Tech I Ship With

  • Languages: Python, JavaScript/TypeScript, SQL, Bash
  • AI / LLM: AWS Bedrock, RAG, evaluation datasets, guardrails, red-team workflows
  • AWS / Serverless: Lambda, DynamoDB, Amazon Connect, Lex, IAM, SSM, CloudWatch
  • Backend / Apps: FastAPI, SQLite, REST APIs, admin tooling
  • Observability / Ops: Datadog APM, CloudWatch, tracing, token/RAG metrics, canary checks, readiness checks
  • Automation / QA: Playwright, pytest, GitHub Actions, structured logging, security checks

What I Build

  • Production GenAI systems — Bedrock-backed workflows, serverless APIs, contact-center automation, observability, and runbooks
  • RAG & evaluation delivery — golden datasets, token/retrieval metrics, latency checks, retry automation, and admin tooling
  • Agent and red-team tooling — browser automation, evidence capture, judge-analysis workflows, reliability harnesses, and safety tests

Delivery Proof

AWS AI Contact Center & Internal Automation (Private)

Designed and shipped Korean-language AI operations systems using Amazon Connect, Lex, Bedrock, Lambda, DynamoDB, and Google Workspace automation. The work included observability and operator runbooks.

RAG, Bedrock Knowledge Base & Evaluation Systems (Private)

Built golden-dataset flows, evaluation guidebooks, latency scripts, retry automation, admin interfaces, and delivery packaging for retrieval systems.

AI Safety, Red-Team & Reliability Tooling (Private)

Built test harnesses, browser automation, evidence capture, judge-analysis workflows, readiness checks, and infrastructure hardening for LLM systems.

LLM Observability & Production Hardening (Private)

Built Datadog/APM instrumentation, tracing guides, token/RAG metrics, canary checks, readiness checks, CloudWatch handoff docs, and incident reports.

Selected Public Artifacts

Public repositories are representative samples. Most production delivery happens in private and organization repositories.

Activity Snapshot

The section below is refreshed automatically from GitHub activity data.

  • Last updated: 2026-04-30
  • 3,226 contributions in the last 12 months
  • 19 pull request contributions and 80 commit contributions
  • 19 owned public repositories and 42 owned private repositories (excluding forks)
  • 3,101 restricted contributions from private and internal work

Working Style

  • Minimal, verifiable changes over flashy complexity
  • Strong bias toward automation, documentation, and repeatable workflows
  • Comfortable moving from prototype exploration to operational delivery
  • Production readiness means metrics, traces, runbooks, and failure evidence — not just demos

Links

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  1. BONMEDIA-News-Research-Tool BONMEDIA-News-Research-Tool Public

    serviceteam_seminar

    Python

  2. OM_VC_chatbot-OM_Vot OM_VC_chatbot-OM_Vot Public

    to practice ChatGPT API

    HTML

  3. used-book-buyback-price-search used-book-buyback-price-search Public

    알라딘과 YES24의 중고도서 매입가를 쉽고 빠르게 비교해보세요!

    HTML

  4. Slackbot_for_Upbit_trading Slackbot_for_Upbit_trading Public

    KU SoC Understanding Blockchain Business class

    Python

  5. TradeData_Automation TradeData_Automation Public

    Jupyter Notebook

  6. LSDS_Gemini LSDS_Gemini Public

    A REST API for detecting phishing URLs in SMS messages, leveraging web scraping, LLM, and threat intelligence services.

    Python