From Network Engineer to Applied AI: Ryan Booth on the Career Path Nobody Maps Out

By Published On: April 29, 2026

Description: Keith sits down with Ryan Booth — former network automation specialist, Apstra alum, and now principal consultant at Blue Ridge Consulting — to trace the real career arc from infrastructure engineer to applied AI practitioner. They dig into the transferable skills that actually matter (hint: it’s not the coding), why curiosity-driven entry points like AI art generation can unlock an entirely new discipline, and what CIOs should prioritize before they start hiring for AI roles. Ryan makes the case that most organizations should be fixing workflows before chasing staffing plans — a perspective that lines up with what we’re hearing in Buyer Room conversations.

The CTO Advisor
The CTO Advisor
From Network Engineer to Applied AI: Ryan Booth on the Career Path Nobody Maps Out
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Show Notes:

Ryan Booth’s career path reads like a compressed version of the last 15 years of enterprise infrastructure evolution: Cisco Networking Academy, CCIE-track networking, network automation, a formative stint at Apstra (pre-Juniper acquisition, pre-HPE), and now building agentic AI applications and advising organizations on applied AI strategy.

In this episode, Keith and Ryan unpack what it actually takes to make that transition — and what CTOs should be looking for in their own teams. Key threads from the conversation:

  • The “Applied AI Engineer” archetype — Ryan describes the emerging role that’s less about building models and more about figuring out how to deploy AI in real operational contexts. The parallel to Cursor’s $60B valuation as an “AI wrapper” is deliberate: making AI practical is the job.
  • Transferable skills from network automation — The Apstra era taught Ryan enterprise-grade software development discipline, cross-team technical leadership, and the integration mindset (Apstra + Terraform) that maps directly onto agentic AI workflows today.
  • The staff engineer inflection point — Ryan identifies the career level where technical depth alone stops being enough. Staff-level engineers need to drive direction across infrastructure, application, and business teams simultaneously. That cross-domain orchestration skill is exactly what applied AI demands.
  • Curiosity as the gateway — Ryan’s honest admission: he bounced off machine learning multiple times before AI art generation gave him a personally compelling entry point. Six months of Saturday morning Colab notebooks preceded ChatGPT’s arrival and made all the difference.
  • Workflows before staffing — When Keith asks how to build AI muscle internally, Ryan redirects: assess your bottlenecks first. AI should reduce overload on existing teams, not trigger a reorg. This echoes the Vail/HPE municipal AI case where the win was summarizing microfiche data, not replacing staff.

Where to find Ryan:

Referenced in this episode:

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