About
Secure, observable, recoverable AI
Building AI systems isn't just about calling a model, it's about creating agents that remember what they learned, check their own work, and hand off cleanly to each other and to the people they serve.
I'm a Senior AI Engineer with 10+ years in enterprise IT, Windows and Linux systems administration, and cloud infrastructure. For the past 3 years I've focused on production RAG pipelines, multi-agent LLM workflows, and fast web apps. I came up through Tier 2 support, server administration, and on-call rotations, so I build AI the way I ran servers: secure by default, observable, and recoverable.
Enterprise RAG
Ingestion, semantic chunking, embeddings, hybrid retrieval, and strict source grounding.
Agent engineering
Structured tool calling, MCP connectors, persistent agent memory, eval harnesses, and human-in-the-loop guardrails.
Cloud & DevOps
AWS, GitHub Actions, CodePipeline, Terraform, Docker, Vercel, and Supabase.
Infrastructure & security
Windows Server, Active Directory, RHEL/Ubuntu, VMware, DISA STIG, CIS, NIST 800-171, SOX, and PCI.