Profile

Backend/Platform & AI Tech Lead Go, AWS, LLMOps Scaled to WAU 4M / MAU 8M Company-wide GenAI rollout (11k+)

Strengths

  • Translating business requirements into system designs
  • End-to-end delivery from requirements to production
  • Breaking down complex problems into actionable plans
  • Designing team development infrastructure and workflows
  • Driving developer productivity and automation
  • Backend/platform engineering and cloud infrastructure

Professional Summary

I have experience in all phases from product launch to operation. I excel at design and development that maximizes outcomes while prioritizing business impact. I’m particularly interested in building systems and infrastructure to achieve higher productivity as a team.

Executive Summary

Backend/Platform & AI Tech Lead (5+ yrs). Led a company-wide GenAI product (11k+ employees) as Engineering Lead/Tech Lead, built LLM evaluation with LangSmith, and shipped on AWS (ECS/DynamoDB). Scaled a retail app to WAU 4M / MAU 8M; improved observability, doubling the maintenance budget. Strong in Go, Python, and AWS with solid LLMOps experience; business-level English for cross-border requirements, presentations, and documentation.

Skills

Technology/Skill Category Experience
Go Languages 5 years
Python Languages 3 years
TypeScript Languages 2 years
PHP Languages 1 year
AWS (ECS, DynamoDB, SQS, ALB, S3 etc) Cloud/Infra 5 years
Azure (OpenAI, Cosmos DB) Cloud/Infra 1 year
Docker Cloud/Infra 5 years
Terraform (IaC) Cloud/Infra 5 years
MySQL Database 5 years
PostgreSQL Database 3 years
Redis Database 3 years
Azure Cosmos DB (MongoDB API) Database 1 year
gRPC / Protocol Buffers Networking & IPC 3 years
GitHub Actions / PipeCD CI/CD 3-5 years
Datadog (APM, Logs, Synthetics) Observability 3 years
LangChain / LangGraph / LangSmith GenAI / LLMOps 2-3 years
Nuxt.js (Vue.js) Framework/Library 2 years

Experience

Skill/Experience Experience
DevOps 3 years
Scrum development 3 years
Tech Lead 2 years
Engineering Manager 2 years
Project management (Agile/Scrum & Waterfall) 2 years
AI-enabled developer tooling & workflows 2 years
LLMOps 2 years
PdM (Product Manager) 1 year

Work Experience

Jun 2025 – Present: DX Project for a Major Retail Company – AI Business Unit

Impact • Scope • Tech

  • Impact: Responsible for designing and developing backend infrastructure supporting large-scale traffic (WAU 4M / MAU 8M). Enabled safe service growth through gradual rollout using feature flags and comprehensive test strategies
  • Scope: Backend engineer in multi-vendor collaboration (4 companies) with PM×6, Backend×4, Frontend×3, Native×4, Designer×2
  • Tech: Go, Docker, MySQL, gRPC, Envoy, Terraform, AWS, Datadog, k6

Key Achievements

  • Scaled backend systems to support a WAU 4M / MAU 8M service
  • Implemented a feature-flag strategy for safe, incremental releases
  • Designed and executed comprehensive test strategies for large-scale services

Feb 2024 – Jun 2025: Cyber AI Scheduler – AI Operations Unit

Impact • Scope • Tech

  • Impact: Won top prize (~2,200 ideas) and achieved company-wide rollout (11k+ employees). Built LLM evaluation (LLM-as-a-judge + LangSmith) that turned “answer quality” into a KPI shared with business, accelerating decisions and releases; presented at CADC2024
  • Scope: Engineering Lead/Tech Lead for PM×1, Engineer×4, Data Scientist×1; led technology selection, architecture design, infrastructure setup, requirements definition, and KPI design
  • Tech: Go, Python (LangChain, LangGraph), LangSmith, Docker, PostgreSQL, gRPC, Envoy, Terraform, AWS (ECS/DynamoDB/VPC/ALB/S3/SQS), Azure OpenAI, Datadog, PipeCD

Key Achievements

  • Architected and shipped GenAI product for 11k+ employees (natural language scheduling)
  • Built LLMOps infrastructure: LLM evaluation with LangSmith, enabling business-aligned KPIs
  • Led tech selection (Azure OpenAI, LangChain); introduced GitHub Codespaces and trunk-based dev
  • Designed AWS infrastructure (ECS, DynamoDB, SQS, OpenSearch) with Terraform and CI/CD (GitHub Actions, PipeCD)
  • Presented at CADC2024 on LLMOps practices for product teams

Note: Top prize in internal GenAI contest with ~2,200 submissions.

Apr 2023 – Present: New Overseas Development Base Establishment – Hanoi Dev Center

Impact • Scope • Tech

  • Impact: Established new development base in Hanoi, Vietnam; contributed to company’s development competitiveness through hiring and training talented local engineers
  • Scope: Responsible for engineering organization management, culture promotion, recruitment strategy, and cross-border team operations
  • Tech: Organization design, recruitment, training, global base operations

Key Achievements

  • Built Vietnam engineering organization from scratch; established hiring pipeline and onboarding processes
  • Drove culture alignment across Japan/Vietnam teams; managed cross-border collaboration
  • Contributed to company’s global competitiveness by scaling engineering talent pool

Apr 2023 – Jan 2024: DX Project for a Major Retail Company – AI Business Unit

Impact • Scope • Tech

  • Impact: Designed coupon feature for 600+ RPS; led load testing & tuning. Built observability (Datadog dashboards/alerts, synthetics, on-call tooling), which was highly valued by the client and doubled the maintenance budget; improved release confidence and MTTR
  • Scope: Backend engineer in multi-vendor collaboration (4 companies) with PM×10, Frontend×5, Backend×5, Native×4, Designer×2; responsible from product launch to production release
  • Tech: Go, Docker, MySQL, gRPC, Envoy, Terraform, AWS, Datadog, k6, PipeCD

Key Achievements

  • Architected a high-performance coupon system for 600+ RPS (concurrency with Goroutines; data-model split for master/user data)
  • Built end-to-end observability (Datadog dashboards/alerts, Synthetics, on-call); improved release confidence/MTTR and doubled the client’s maintenance budget
  • Led load-testing strategy with k6 and performance tuning; ensured production readiness at scale

Apr 2021 – Mar 2023: Remotenashi – AI Business Unit

Impact • Scope • Tech

  • Impact: Developed online customer service tool for hospitality DX from internal new business proposal contest to commercialization. Completed full migration from Nuxt2 to Vue3 after evaluating Nuxt3 beta. Released new features including real-time product proposal functionality by uncovering latent client needs
  • Scope: Full-stack engineer in team of PM/Sales×7, Designer×1, Engineer×10; responsible end-to-end from requirements/design definition to implementation
  • Tech: Go, Docker, MySQL, Terraform, AWS, TypeScript, Nuxt.js (Vue.js), Vite, Bucketeer, WebSocket, Pinia

Key Achievements

  • Led Nuxt3 beta evaluation and independently executed full Nuxt2 → Vue3 migration
  • Designed and shipped real-time product proposal feature (WebSocket + Pinia) enabling live commerce experience
  • Collaborated across disciplines (design/business) to extract client needs and drive feature proposals from requirements to release
  • Built full-stack features end-to-end: requirements, UI/UX design (Figma), implementation, and production deployment

Side Work

May 2025 – Aug 2025: AI Development Project for Patent Analysis at a Major Chemical Company – Galirage, Inc.

Impact • Scope • Tech

  • Impact: Built RAG system in highly specialized domain (patent documents); translated client needs into product specifications and drove product development after PoC completion
  • Scope: Generative AI engineer in team of PM×1 and Engineer×4, responsible for designing and implementing patent analysis AI agent
  • Tech: Python (Streamlit, LangChain, LangGraph), LangSmith, Azure, PostgreSQL, Docker

Key Achievements

  • Built a production-ready RAG system for patent literature (domain-specific retrieval; evaluation via LangSmith with LLM-as-a-judge and rubric-based scoring), bridging client requirements to technical specs post-PoC as the Generative AI engineer

Jan 2025 – May 2025: Development of Raggle and Competition Hosting – Galirage, Inc.

Impact • Scope • Tech

  • Impact: Hosted RAG answer accuracy competitions with ~150 participants per event; built evaluation infrastructure and established product quality improvement cycle through user analysis
  • Scope: PdM and Tech Lead working with CS×1, responsible for product vision, development roadmap, and evaluation infrastructure design
  • Tech: Python (Streamlit, LangChain), LangSmith, Firebase, GCP, Docker, Rollbar

Key Achievements

  • Built evaluation pipeline for RAG competition platform (LLM-as-a-judge, LangSmith)
  • Led product vision and roadmap as PdM; drove data-informed iterations
  • Scaled competition hosting to ~150 participants with automated scoring infrastructure

Output

Past Presentation Materials

Blog posts