Infrastructure · Security · Education
Building the operational infrastructure for autonomous AI agents.
Three decades of enterprise technology experience — from Cisco networking to AI agent systems. Designing the tools, security frameworks, and platforms that make production-grade AI agents reliable and accessible.
Combining deep enterprise infrastructure knowledge with modern AI systems engineering to build production-grade agent platforms.
Designing multi-agent systems with tool orchestration, memory management, and autonomous decision-making for enterprise workflows.
Prompt injection defense, input/output guardrails, PII filtering, and safety frameworks for production LLM deployments.
Container orchestration, fleet management, secrets handling, and operational tooling for running agents at scale.
Three decades of Cisco architecture — routing, switching, security, and network automation. Five CCIE certifications.
Building reliable, observable platforms with real-time monitoring, cron scheduling, and cross-service communication.
Global-scale training program design. Translating complex systems into accessible, hands-on learning experiences.
A career built on making complex technology accessible — starting with networks, now extending to AI.
Designing and building operational platforms for autonomous AI agents. Focused on agent orchestration, LLM security, and making agent technology production-ready for enterprise adoption.
Founded and scaled one of the largest Cisco training organizations globally. Built instructor-led and digital education programs serving enterprise clients across 40+ countries. Successfully exited to private equity.
Traveled internationally delivering advanced Cisco networking training. Earned five CCIE certifications — among the most certified Cisco engineers worldwide.
Early career at Cisco headquarters during the foundational years of enterprise networking.
Open-source tools and platforms for building, managing, and securing AI agent systems.
Real-time operational dashboard for AI agents. Live activity feeds, sub-agent monitoring, cron scheduling, and context-aware search across agent memory and sessions.
Input/output security layer for large language models. Prompt injection detection, PII filtering, content guardrails, and real-time threat monitoring for production deployments.
Container-based orchestration for multi-agent deployments. Centralized secrets management, resource isolation, and automated scaling across cloud and edge environments.
Interested in AI agent infrastructure, LLM security, or technical education? I'm always open to connecting with builders and engineers working on the next generation of AI systems.