CV

Yan Paing Oo

AI Engineer & DevOps

yanpaingoo.dev · LinkedIn · GitHub · me@yanpaingoo.dev · WhatsApp

AI Engineer with a Computer Science degree in Knowledge Engineering (AI, ML, Computer Vision) and 2+ years of production experience shipping LLM-powered systems. Delivered multi-agent chatbot architectures, RAG pipelines, and tool-calling agent systems across two companies. Strong DevOps background — AWS infrastructure, CI/CD, containerization, and cloud architecture (GCP certified).

Skills

Area	Technologies
AI / LLM	Multi-agent systems, tool-calling agents, RAG, context engineering, prompt design, LLM benchmarking, embeddings, vector search, LangChain, streaming conversations
Models	Gemini, ChatGPT, Mistral, Ollama, CloudWeGo Eino, Google GenAI SDK
Cloud / DevOps	AWS (ECS, EC2, S3, RDS, CloudFront, Route53), GCP, Docker, Kubernetes, Terraform, Ansible, GitHub Actions, GitLab CI, Nginx
Backend	Go, Node.js, TypeScript, NestJS, PostgreSQL, MongoDB, REST API, WebSockets
Frontend	React, Next.js, Vite, Shadcn UI, TanStack

Experience

AI Engineer & DevOps — Aug 2025 – Present

Pluggi

Production chatbot struggled at 10K+ U.S. user scale. Architected AWS load balancing with Nginx reverse proxy on reserved EC2 instances and spot on-demand nodes. User complaints reduced 50%, uptime improved from 97% to 99% at only 0.57% cost increase.
Chatbot needed specialized domain knowledge across 4 areas. Engineered multi-agent LLM system with domain-specialized sub-agents and tool-calling. Achieved 100% tool accuracy and 20% token reduction on 55-case benchmark suite.
LLM agents produced inconsistent reasoning from unstructured tool outputs. Formulated structured response formats (SUMMARY + DATA + GUIDANCE). Agent quality score improved from 4.7 to 5.0/5.
Platform had no backend infrastructure. Led architecture from the ground up with NestJS. System now handles 500+ daily active conversations.

Software Engineer & DevOps (Part-time → Full-time) — Feb 2025 – Jul 2025

Pluggi

Pluggi had zero technical infrastructure at founding. Established entire tech stack as first engineer — backend, infra, CI/CD, deployment. Company launched on production-ready stack.
Non-technical staff depended on engineers to deploy chatbot workflows. Built in-house bot-system builder with React Flow visual UI. Workflow deployment speed increased 3x for non-technical users.
Complex chatbot flows had unreliable state transitions. Co-authored state management system using XState with custom extensions. Stabilized flow execution and mentored 2 junior developers.

Associate Software Engineer — Feb 2024 – Jan 2025

Brillar Pte. Ltd.

Chatbot responses were slow and limited to single model/channel. Delivered LangChain-powered solutions integrating ChatGPT, Gemini, and Mistral with real-time streaming across 3 channels. Response latency reduced 20%.
Gen-AI team’s manual deployments were slow and error-prone. Implemented CI/CD pipelines with GitHub Actions and Docker. Deployment cycle reduced 30%.
Mobile testing across 50+ devices required manual coordination. Built real-time testing platform integrating Appium (Android & iOS), Selenium, and Tosca. Enabled automated parallel testing across 50+ devices.

Freelance Full-Stack Developer & Infrastructure Consultant — May 2023 – Feb 2024

4 clients needed custom inventory and financial tracking systems. Engineered full-stack Warehouse Management System and Car Ledger Software with inventory tracking and financial logging. Delivered all 4 projects to production.
Ledger systems needed to handle high transaction volumes. Built high-performance Go microservices for data-heavy processing. System handled 100K+ daily transactions.
Small business clients had no cloud infrastructure or backup strategy. Managed end-to-end deployment — Nginx, SSL, automated backups. Clients gained reliable, secured production environments.

Automation & Performance Engineer — Aug 2022 – May 2023