Real-time AI Voice Receptionist
Missed after-hours and overflow calls → captured bookings with sub-300ms voice responses that felt live.
AI Systems Architect · Forward Deployed Engineer
I deploy production AI agents for enterprise customers and own delivery end to end, from discovery and success criteria through proof of concept to production.
I design and deploy production AI agent systems for SMB and enterprise clients, owning the full lifecycle from requirements and success criteria through proof of concept to production. Voice and chat agents, RAG pipelines, and multi-agent sales-ops, built so teams actually adopt them.
I delivered tailored proofs of concept and technical demos for enterprise observability customers, turning complex telemetry into clear business outcomes and partnering with engineering on pipeline reliability.
I designed multi-cloud solutions across AWS, Azure, and DRaaS for regulated industries, and automated proposal and RFP workflows.
I managed SAN and storage infrastructure with secure access controls, and led technical workshops and reliability initiatives.
I built SAN monitoring dashboards aligned with DoD-7 compliance, and automated reporting and provisioning.
Twenty-one production systems across eight clients. Each one is real, anonymized by industry, which is standard under NDA.
Missed after-hours and overflow calls → captured bookings with sub-300ms voice responses that felt live.
Hours of hand-built illustrations and paperwork → roughly 85% less manual prep per client.
Leads slipping through the cracks → near-instant response, with the team working only qualified leads.
Tribal knowledge buried in docs → fewer repeat questions and faster onboarding for new hires.
Reps buried in research and drafting → time back for real conversations, not busywork.
Shoppers asking what a static site could not answer → higher engagement and qualified leads off the site.
Slow, error-prone manual review → roughly 85% less review, with humans on exceptions only.
Every build starting from scratch → faster, more consistent deployments across clients.