Graham's Career Vision
This page follows the Never Search Alone framework by Phyl Terry. It's designed to articulate who I am, what I'm looking for, and where I'm headed—clearly and authentically.
Candidate Market Fit
The 10-second answer to "What do you do?"
AutoCon4 Network Automation for Gigawatt Scale AI Datacenters.
What I'm Looking For
The environment where I thrive
Work Style
Full-time remote work. An online-first company culture that understands things like audio and video quality for calls. That excels using asynchronous tools.
Company Culture
A company that really "gets it" when it comes to using computers and the internet, and is able to have healthy work habits online.
AI Forward
A company excited about AI and that has put considerable thought into the coming AI revolution and what that will mean for the future of work.
Impact
I want to make a positive impact and work to make solutions rather than to make systemic problems worse.
Career Goals
Specific, Measurable, Achievable, Relevant, Time-bound objectives that guide my job search.
Short-Term Goal (Next 6-12 months)
AutoCon4 style Network Automation for companies that need it, beginning work by the end of January 2026.
Long-Term Goal (3-5 years)
Getting my first expert level certification.
What I Bring to the Table
A summary of skills, experience, and qualities—extracted from 10+ years of network engineering and Python development.
Network Engineering
Deep expertise in Juniper (MX/SRX, JNCIP-SP) and Cisco (ACI, Catalyst, ASR 9k, Nexus). BGP, OSPF, MPLS, VXLAN/EVPN, and service provider architectures.
Automation & DevOps
Python tooling (PyATS, Netmiko, NAPALM, Paramiko), Git workflows, CI/CD pipelines, and infrastructure-as-code practices.
Teaching & Communication
Designed and taught a 40-hour Python for Network Engineers course. ~1,000 educational videos on YouTube. Clear technical communication.
Continuous Learning
Active learner across cloud platforms (AWS/Azure/GCP), AI tooling, and emerging network technologies.
The Narrative
Graham Paasch represents a decade of network engineering evolution—from traditional ISP infrastructure at Charter Communications to cutting-edge FTTH automation at Google Fiber. The throughline: an increasing drive toward automation, code-driven infrastructure, and teaching others to do the same.
What distinguishes this profile is the intersection of deep protocol expertise (BGP, MPLS, EVPN-VXLAN) with genuine software engineering practices. Not just scripts that work, but tested, version-controlled, CI/CD-integrated tooling. The recent transition to teaching—designing a 40-hour Python for Network Engineers curriculum—signals someone who has internalized this knowledge deeply enough to transfer it.
The timing matters. AI datacenters are scaling to gigawatt power draws. The network automation skills forged in service provider and hyperscaler environments are exactly what these facilities need. Graham is positioning at the intersection of proven NetDevOps capability and the infrastructure buildout of the decade.
Connect
Ready to discuss network automation for AI infrastructure? Reach out.