Endpoint management that actually holds up in the real world.
I'm Michael Singletary — Senior Enterprise Endpoint Management Engineer. I specialize in Jamf Pro architecture, macOS fleet management, and applying AI practically to endpoint operations. I build systems designed to stay organized, maintainable, and understandable long after the initial rollout.
MS
Apple management that scales without becoming a mystery.
I specialize in environments where the stakes are real — large macOS fleets, diverse users, compliance requirements, and a team that has to be able to pick up where I left off.
Jamf Pro Architecture & Fleet Management
Designing smart group logic, policy structures, configuration profiles, and extension attributes that remain legible as environments grow. I build for what happens when your fleet triples — not just what works today.
macOS Management Strategy
Balancing security posture, user experience, and operational overhead across enrollment, app delivery, OS update readiness, and configuration. The goal is a fleet that's secure and supportable — not just locked down.
Identity & Access Alignment
Implementing Platform SSO, account alignment, and authentication flows that reduce confusion for users and support teams alike. Modern Apple identity management shouldn't require a help desk ticket to explain.
Higher Education Context
University environments bring a unique blend: research machines, classroom labs, BYOD, compliance mandates, and a user base spanning first-year students to senior faculty. I understand that balance.
Operational discipline over clever one-liners.
The environments that hold up under pressure are designed with maintainability in mind from the start — not patched together after the fact.
🧩 Structure over entropy
I break complex problems into policies, rollout phases, and documentation any team member can follow — even under pressure. A well-structured Jamf environment shouldn't require tribal knowledge to operate.
🔁 Staged, reversible deployments
Every workflow I build is designed to be tested incrementally and rolled back if needed. Irreversible changes in production are a design failure, not an acceptable tradeoff.
⚡ Automation with guardrails
Scripting and API work should remove toil without trading visibility for convenience. I automate carefully — with logging, error handling, and a clear picture of what happens when things go sideways.
📖 Documentation as a deliverable
If a process isn't documented, it doesn't exist. Clear runbooks, smart group annotations, and policy comments are part of the work — not afterthoughts to be written someday.
A multiplier — not a replacement for experience.
I use AI daily in endpoint work, but I've thought carefully about where it earns trust and where it needs a leash. Context and verification are what make it actually useful.
Those who get the most value from AI are the ones who know enough to catch its mistakes. Raw output is a starting point — production experience is still what validates it.
Context-first prompting
Environment constraints, Jamf version, policy scope, and desired behavior upfront — AI output that fits your specific fleet, not a generic answer.
Script & policy drafting
Using AI to iterate on extension attribute logic, shell scripts, and smart group criteria — then reviewing and adapting before any deployment.
Troubleshooting acceleration
Feeding log output and policy structure to surface hypotheses faster — then testing those hypotheses in a controlled scope before acting fleet-wide.
Documentation drafting
Turning implementation notes into clean runbooks with AI as first-pass writer — then editing for accuracy and the institutional knowledge only experience provides.
Let's talk endpoint management.
Whether it's Jamf architecture, macOS management strategy, AI in IT operations, or something specific to higher ed — I'm happy to connect.