About
By day I'm a senior network and security engineer. Most of my time goes to designing and deploying scalable, secure infrastructure across a handful of sites and the cloud — and keeping all of it lined up with our cybersecurity baseline. Here's roughly what that looks like:
- Multi-site build-outs — server rooms, data closets, UPS, fiber patch panels, handoff/core/access switching and wireless.
- Dual-hub & spoke interconnecting physical sites and cloud.
- SD-WAN across all ISP links with traffic shaping & QoS.
- Day-to-day maintenance and network documentation.
- Zero Trust — microsegmentation, device posture, RBAC, least privilege, RBI, DNS filtering, TLS.
- IPS for deep packet inspection; SIEM + SOAR for security event management.
- AI security guardrails — shadow AI, CASB, RBI.
- WAF for origin protection — rate limiting, geolocation.
Want the formal version? Read my full résumé →
Personal projects
The fun stuff — home lab notes and whatever I've been building on the side. These two are just placeholders for now; I'll drop in the real write-ups as they're ready.
Home lab topology
Describe the rack, hypervisor, VLAN layout and what you use it to test.
Project two
Add a short summary and a link to the full write-up.
The library so far
Everything I've written up, grouped by vendor. It's all sanitized — the hostnames, public IPs and keys are made up — so nothing here maps to a real network. More gets added whenever I get around to it.
Azure
Cisco
Cloudflare
Fortinet
Cybersecurity
Threat-hunting and defensive notes that aren't tied to one vendor. The first one is about spotting phishing sites that wear your domain name. It's all sanitized, with placeholder domains throughout.
Phishing & brand protection
AI Governance
Notes on keeping AI use sane and safe — mostly around shadow AI control: spotting the tools people quietly start using, putting guardrails around them, and making sure nothing sensitive leaks into a chatbot. Still a work in progress; these are the write-ups I'm planning.
Finding shadow AI
How to see which AI tools are actually in use before you try to govern them.
Guardrails & acceptable use
Pairing a plain-English AUP with controls that actually enforce it.
RBI for AI tools
Using remote browser isolation to let people use AI without it touching the endpoint.
DLP for prompts & uploads
Stopping API keys, source and customer data from being pasted into a prompt.