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Full-Stack Developer with 5 years of experience specializing in Python, AWS, and AI/LLM applications, delivering production-grade backend systems, ETL pipelines, and AI platforms (from RAG web apps to a grounded multi-tenant teaching assistant used daily by teachers). Experienced in infrastructure migration to containerized/scalable environments using Terraform, Docker, and Kubernetes on AWS, with a strong focus on automation, code quality, and reliable CI/CD.…Full-Stack Developer with 5 years of experience specializing in Python, AWS, and AI/LLM applications, delivering production-grade backend systems, ETL pipelines, and AI platforms (from RAG web apps to a grounded multi-tenant teaching assistant used daily by teachers). Experienced in infrastructure migration to containerized/scalable environments using Terraform, Docker, and Kubernetes on AWS, with a strong focus on automation, code quality, and reliable CI/CD.

Minh Tang Ba

Full Stack Developer, Web Developer, Back-End Developer, +2

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Full-Stack Developer with 5 years of experience specializing in Python, AWS, and AI/LLM applications, delivering production-grade backend systems, ETL pipelines, and AI platforms (from RAG web apps to a grounded multi-tenant teaching assistant used daily by teachers). Experienced in infrastructure migration to containerized/scalable environments using Terraform, Docker, and Kubernetes on AWS, with a strong focus on automation, code quality, and reliable CI/CD.…Full-Stack Developer with 5 years of experience specializing in Python, AWS, and AI/LLM applications, delivering production-grade backend systems, ETL pipelines, and AI platforms (from RAG web apps to a grounded multi-tenant teaching assistant used daily by teachers). Experienced in infrastructure migration to containerized/scalable environments using Terraform, Docker, and Kubernetes on AWS, with a strong focus on automation, code quality, and reliable CI/CD.

Available to hire

Full-Stack Developer with 5 years of experience specializing in Python, AWS, and AI/LLM applications, delivering production-grade backend systems, ETL pipelines, and AI platforms (from RAG web apps to a grounded multi-tenant teaching assistant used daily by teachers).

Experienced in infrastructure migration to containerized/scalable environments using Terraform, Docker, and Kubernetes on AWS, with a strong focus on automation, code quality, and reliable CI/CD.

Skills

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Expert

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Intermediate

Language

Work Experience

In AI Teaching Assistant for Border-School Teachers (Team Leader) at Guangxi Normal University-backed research group

April 1, 2026 - Present

Architected a grounded AI teaching-assistant platform used by 37 border schools and 1,200+ teachers. Enabled teachers to generate curriculum-aligned, audit-ready lesson packages quickly, including plan/PPT/exams/scripts and quiz games rendered safely in-chat. Built searchable compliant content using LightRAG and multi-corpus retrieval, plus a two-gate compliance system that fails closed for risky output. Implemented multi-tenant per-teacher sandboxing with isolated Docker execution, and agentic engineering with shared deployments, container image pinning, GitOps-based CI/CD, Playwright E2E/backend tests, and DR runbooks. Tech: Vue.js, FastAPI, PostgreSQL (pgvector + AGE), Redis, vLLM, LiteLLM, LightRAG, DeerFlow, Celery, K3s, ArgoCD, Jenkins, MinIO, OpenTelemetry.

Inference Platform (Elastic GPU inference for LLM & image workloads) at AWS spot-based GPU inference platform

January 1, 2026 - Present

Built an elastic, spot-first inference platform to reduce fixed GPU costs. Used Terraform and Packer to provision GPU clusters on EKS/Karpenter and KEDA to scale nodes down to zero when idle while scaling up on request. Included fast cold-start via a custom Packer-baked GPU AMI and persistent model cache, with reproducible ArgoCD GitOps. Tech: Terraform, Packer, EKS + Karpenter, vLLM, KEDA HTTP add-on, ALB, EBS, ArgoCD, Cloudflare.

Software Engineer at Pelago.co by Singapore Airlines

February 1, 2025 - May 31, 2026

Owned and maintained high-volume travel partner integrations, including the KKday sync processing 2,000+ bookings monthly, ensuring data consistency for booking, pricing, and availability systems. Led AI-assisted development for a new partner integration with a prompting framework that reduced engineering effort by 50% while preserving core maintenance. Delivered the eSIM integration with Frewie end-to-end using AI-assisted development plus test-driven development. Contributed to the core Supply team integrating third-party travel platforms. Tech: Python, Flask, Celery, Elasticsearch, Redis, PostgreSQL, Docker.

Full-stack Developer at Den AI Canada

May 1, 2024 - February 28, 2025

Collaborated in an agile team to develop and launch a new RAG-based AI web application from concept to deployment. Engineered an AWS infrastructure migration from Beanstalk to a multi-environment setup (dev/stg/prod) using Terraform and Amazon ECS to improve deployment reliability. Established CI/CD pipelines with GitHub Actions to automate testing and deployment and accelerate release cycles. Tech: Next.js, Django REST, LangChain, PostgreSQL, Qdrant, Terraform, AWS ECS.

Backend Developer (Contractor) at FPT Software (for Pelago.co)

November 1, 2023 - October 31, 2024

Built a robust data synchronization pipeline to integrate 200,000+ products from Viator.com. Implemented complex transformations for product, pricing, and availability using Celery for asynchronous processing in a high-traffic environment. Performed code reviews and provided feedback to improve team code quality. Tech: Celery, Python, SQL (plus internal services).

System Development Engineer at FLINTERS Vietnam

December 1, 2021 - November 30, 2023

Designed and implemented scalable AWS batch ETL pipelines for large advertising datasets powering an AI Click-Through Rate (CTR) prediction product. Diagnosed and resolved a critical memory consumption issue in a core XAI deep learning model using Memray profiling, earning commendation from senior technical leads. Re-architected a web scraping pipeline for 30,000 URLs using asyncio, aiohttp, and a Squid cache proxy, reducing processing time by 95% (from 1 week to 8 hours). Tech: Python, SQL, Digdag, Snowflake, AWS Batch/S3, Docker, Django, FastAPI, React.