I'm Eddie Chan — an AI Engineering Manager based in 🇭🇰 Hong Kong, living on coffee and commits.
- 🧠 Managing an AI Engineering Team — shipping production ML/AI systems at scale
- 🏗️ Designing cloud-native infra on AWS with Terraform, Kubernetes & Helm
- 📊 Building data pipelines across Snowflake, Databricks & BigQuery
- 🤖 Driving LLM adoption and AI-assisted development org-wide
- 🎓 HKUST MBA (Class of 2022)
- ☁️ AWS Solutions Architect – Associate · AWS Community Builder
- 📖 Curating AI-generated learning curricula to democratise tech education
- ⏱️ GitHub member since 2016
| Period | Role |
|---|---|
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AI Engineering Team Manager |
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Senior AI Engineer |
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Data Scientist — Early-stage Startup |
As AI Engineering Team Manager 2025 – Present
- 🚀 Defining and executing the AI engineering roadmap end-to-end
- 🏗️ Infrastructure-as-Code with Terraform + AWS (EC2, Lambda, ECS, S3, RDS)
- ☸️ Container orchestration via Kubernetes & Helm chart management
- 📊 Enterprise data engineering across Snowflake, Databricks, BigQuery, Redshift
- 👥 Mentoring engineers, conducting code reviews, hiring and growing the team
- 🔄 Building automation pipelines with n8n for business process optimisation
As Senior AI Engineer 2021 – 2025
- 🤖 Designed and deployed production ML models using TensorFlow and PyTorch
- 🐍 Built end-to-end ML pipelines in Python — from data preprocessing to model serving
- ☁️ Leveraged AWS services (SageMaker, Lambda, EC2, S3) for scalable model deployment
- 🔬 Applied deep learning, NLP, and computer vision techniques to real-world problems
- 📦 Containerised and shipped ML services with Docker and Kubernetes
- ⚡ Optimised model inference performance for production latency requirements
As Data Scientist 2019 – 2021
- 📈 Built predictive models and data-driven product features at a startup
- 🔍 End-to-end ownership: data wrangling, modelling, evaluation, and deployment
- 🐍 Core stack: Python, SQL, scikit-learn
| 🏫 Education | ☁️ Certifications |
|---|---|
|
Master of Business Administration (MBA) Hong Kong University of Science & Technology (HKUST) Class of 2022 |
🏅 AWS Solutions Architect – Associate Amazon Web Services · Cloud Architecture 🏗️ AWS Community Builder Amazon Web Services · Cloud Infrastructure track |
Languages
Cloud & DevOps
ML & AI
Data Engineering
🔥 Hot projects I'm actively hacking on right now
| Project | Description | Stack |
|---|---|---|
| 🔥 terraform-viz | Interactive Terraform plan visualiser — graph explorer, cost estimator & AI insights | TypeScript · Next.js · Vitest |
| 🔥 Hermes-Agent-Cloud | One command. Three clouds. Deploy your AI assistant to AWS/Azure/GCP | Bash · Terraform · Multi-cloud |
| 🔥 AgentFoundry | Agent scaffolding framework for rapidly building & deploying AI agents | Python · LLM · Agent Orchestration |
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Interactive Terraform plan visualiser with a live 2D/3D graph, per-resource cost estimates, AI-powered insights, and a multi-service monorepo architecture. Features: Upload any
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Agent scaffolding framework for rapidly building, composing, and deploying AI agents. Designed for engineers who want production-grade agent infrastructure without the boilerplate.
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One command. Three clouds. Four LLM providers. Deploy the Hermes Agent to AWS, Azure, or GCP with a wizard-first CLI — zero plaintext secrets, zero manual infra wiring. Supports: OpenRouter · OpenAI · Anthropic · Google Gemini | Clouds: AWS EC2 · Azure VM · GCP Compute Engine
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A serverless, OpenAI-compatible LLM gateway on AWS. Drop it in front of any LLM provider and get streaming responses, multi-provider weighted routing, per-tenant rate limiting, and async request logging — all without managing servers. Supports: OpenAI · AWS Bedrock (Nova, Claude) · Anthropic · Gemini · Vertex AI · any OpenAI-compatible endpoint
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Self-paced Python learning course with all content generated by AI. A unique approach to democratising programming education.
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Interactive, browser-based Helm chart renderer and Kubernetes resource graph — no Helm CLI or cluster access required.
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A 26-week self-paced course covering Snowflake, Databricks, BigQuery, and Amazon Redshift — from basics to production pipelines.
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Terraform-powered fast setup for n8n automation on AWS EC2. Spin up workflow automation infrastructure in minutes.
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Passionate about democratising tech knowledge through AI-generated curricula.
| 📘 Resource | Description |
|---|---|
| learn-python-with-ai | AI-generated, self-paced Python course from fundamentals to advanced patterns |
| learn-big-data-with-ai | 26-week curriculum covering Snowflake, Databricks, BigQuery & Redshift |
| n8n Terraform EC2 Fast Setup | Spin up n8n workflow automation on AWS EC2 with Terraform in minutes |
| Helm Visualizer | Browser-based Helm chart renderer — visualise K8s resources without a cluster |
☕ Coffee & Code made my day · Built with passion by Caffeine Coder · Hong Kong 🇭🇰