Building Intelligent Infrastructure

From IP networks to neural networks

My Story

For over 12 years, I've built and operated enterprise network infrastructure — routing protocols, wireless architectures, and zero-trust security — while also working across Linux, storage, virtualization, and cloud platforms — Google Cloud, Azure, and now Cloudflare, which powers this site. As a pre-sales Solutions Architect, I translate technical complexity into business outcomes. But I always felt there was more we could do with automation.

Then AI happened. Not the hype, but the real capabilities of LLMs and agentic systems. I saw an opportunity to bridge two worlds: the deep infrastructure knowledge most AI developers don't have, and the modern AI capabilities most infrastructure engineers haven't explored.

01

The Foundation: Network Infrastructure

I began my career building enterprise networks across many verticals. Over 12 years in pre-sales, I learned that production systems require more than technical specifications — they demand reliability, security, and operational excellence. I earned my CISSP, CCNP, KCNA, and multiple wireless certifications while specializing in RUCKUS wireless architecture and zero-trust security implementations.

02

The Pivot: Discovering AI

After completing Stanford's Machine Learning specialization, I built my first AI agent for network automation using Claude. This experience revealed the potential of combining deep infrastructure knowledge with AI capabilities. I immediately began experimenting with RAG systems, autonomous agents, and agentic workflows that could solve real infrastructure challenges.

03

Open Source & Community

I share selected tools as open source on GitHub: autonomous agents for support automation, RAG-powered knowledge systems, and zero-touch provisioning platforms. Projects like ruckus-ztp and osticket-agent have gained community traction, validating demand for this intersection of infrastructure expertise and AI. Open source has been essential for learning, collaboration, and demonstrating real-world capabilities.

04

What's Next

I'm expanding into iOS development with Swift, focusing on Apple Intelligence and frontier model integration (Claude, GPT, Gemini) for native mobile experiences. I document the technical challenges as I learn. I'm looking forward to applying agentic AI to network management and cybersecurity challenges.

Core Technologies

AI & Development

Python FastAPI Claude OpenAI RAG Vector Databases LangChain Swift/iOS System Architecture

Infrastructure & Security

CISSP Zero Trust BGP/OSPF/MPLS RUCKUS Wireless Architecture Network Automation ZTP Protocol Analysis Linux Virtualization Storage

Cloud & Infrastructure

AWS GCP Azure Cloudflare Kubernetes Docker Terraform CI/CD Prometheus Grafana

Approach to AI Development

I believe AI systems that interact with production infrastructure must be built with safety as a first principle. My autonomous agents include guardrails, approval workflows, and comprehensive logging because reliable AI is responsible AI.

  • ✓ Human-in-the-loop for destructive or irreversible actions
  • ✓ Comprehensive audit logging for all AI decisions
  • ✓ Graceful degradation when facing uncertainty
  • ✓ Explicit approval workflows for production changes

Certifications & Education

Security & AI

Cloud & Networking

  • Kubernetes and Cloud Native Associate (CNCF)
  • CCNP (Cisco)
  • Certified Wireless Design Professional (CWDP)
  • Certified Wireless Security Professional (CWSP)
  • Ekahau Certified Survey Engineer

Let's Connect

Interested in collaborating on open source projects or discussing AI and network automation?

Get in Touch