Lead Information Security Engineer
I'm Johnny Leuthard. I lead CyberArk engineering on one of the largest privileged access platforms in financial services, and I build AI-assisted workflows with Claude, the Model Workspace Protocol, and Interpretable Context Methodology that take the grind out of security work.
Selected work
500+ application teams needed to plug into CyberArk's Central Credential Provider without waiting on engineering. I built the documentation hub that let them do it themselves: setup guides, working code samples, common errors with fixes, and a weekly open Q&A. It became the foundation for the enterprise credential-management maturity program.
Ask me about itLarge CyberArk configuration changes used to take Operations days of manual GUI work. I replaced those workflows with scripted overnight runs and cut implementation time by about half. One deployment script now rebuilds 100+ microservice instances, including services, firewall rules, ACLs, and validation, in about five minutes.
Ask me about itA personal Claude project built with the Model Workspace Protocol. It pulls CyberArk API documentation by version, diffs every endpoint, and generates HTML and PDF reports tuned for managers, developers, or platform engineers. Hours of manual doc review now run on demand in minutes.
Ask me about itResume
Every role built toward the same thing — securing access at scale, then automating the parts that shouldn't need a human. Here's the path.
Lead technical direction and mentoring across a 15–20 person CyberArk Engineering group on a platform holding 700,000+ privileged accounts across 60,000+ safes — one of the largest CyberArk deployments in financial services. Built the self-service CCP onboarding hub that let 500+ application teams onboard independently, engineered the PowerShell automation suite that cut implementation time roughly 50%, and serve as primary technical liaison during audits.
Ran the competitive assessment that led Bank of America to select CyberArk as its enterprise PAM platform, then designed and deployed CyberArk infrastructure (CPM, PSM, PVWA, AIM, CCP) from the ground up. Managed vaulting of 200,000+ privileged credentials and automated remediation of 10,000+ file shares with incorrect permissions.
Supported 1,700+ Wintel servers across legacy and enterprise environments. Partnered with Legal on 2–3+ eDiscovery collections a month, including terabyte-scale data pulls, and kept production data in sync through major file and print server migrations.
Installed and commissioned multi-node Windows Server print systems at customer sites nationwide for high-volume industrial digital printing. Diagnosed field issues, reproduced them in the lab, and coordinated fix cycles with the development team.
Managed end-to-end installation projects for new dental office openings nationwide — building, testing, and deploying complete workstation and network environments, then training staff on-site.
Capabilities
Learn
I build my AI workflows in the open using Interpretable Context Methodology (ICM) and the Model Workspace Protocol (MWP) — structured, reviewable context systems for working with Claude on real engineering problems. Check out the repos, fork what's useful, and see how the CyberArk API change reporter and other projects are put together.
Clief Notes is the Skool community where I'm learning AI automation, n8n, and prompt engineering alongside other builders. There's a genuinely deep library of free content, courses, and discussion, no payment required to get real value. If you decide to go further and join a paid track, using my link gives me a small kickback at no extra cost to you.
About
I've spent 30 years in IT and security, the last 15 deep in privileged access management. I helped select and deploy CyberArk at one top-5 US bank, then built and led engineering at another: a platform holding 700,000+ privileged accounts across 60,000+ safes, with a 15-to-20 person engineering team I mentor and guide.
The next chapter is AI. I build structured AI workflows with Claude, the Model Workspace Protocol, and Interpretable Context Methodology: audit reporting that starts from a plain-English question, API change analysis that runs itself, and automation pipelines in n8n. The plan is simple. Deliver on day one with CyberArk depth, and build the AI layer on top of it.