Hey there 👋
I'm Afraz Ahmed, a Staff Engineer at DigitalOcean who spent a decade in infrastructure before realizing AI systems need people who actually understand production reliability.
What I'm Working On
Currently building AI systems that process 800+ customer conversations daily at Cloudways. The kind that actually ship to production and stay running.
Recent projects:
- 🤖 AI QA Agent - Multi-agent system with >90% efficiency increase for our QA team. Redis queues, PII sanitization, the works.
- 🛠️ Cloudways Co-pilot - Natural language server management with a safety-first approach (because nobody wants AI accidentally nuking production)
- 🧠 RAG Pipeline - RAPTOR-based knowledge system that doesn't hallucinate customer support answers
- 🔗 MCP Server - 43 tools covering the full Cloudways API with proper encryption and async architecture
The Tech Stack
AI/ML: Python, Google ADK Framework, Multi-Agent Systems, RAG Pipelines, FAISS, Model Context Protocol
Infrastructure Foundation: Kubernetes, Docker, CI/CD (GitHub Actions, ArgoCD), Linux, AWS, GCP, DigitalOcean
Services & Tools: Redis, MariaDB, Nginx, Apache, Varnish, ProxySQL, Terraform, Bash scripting that actually works
Philosophy
Most people talk about AI potential. I prefer shipping production systems that solve actual problems and stay running at 3 AM.
My infrastructure background means the AI systems I build don't just work in demos—they handle real load, fail gracefully, and have proper monitoring. Because what's the point of intelligent automation if it needs constant babysitting?
Background
- 📍 Based in Karachi, Pakistan
- 💼 15+ years: Started with Windows/Networking/Datacenter Management, evolved through Linux system management, Kubernetes orchestration, and now AI systems
- 🎯 Current focus: Building multi-agent AI platforms that actually scale
- 📊 Results-driven: If it doesn't have measurable impact, I'm not interested
Let's Connect
- 📧 aphraz@live.com
- 🌐 Opinions are my own (obviously)
Building AI systems that turn hype into measurable business outcomes. One production deployment at a time.