AI engineer and Marine Corps veteran who designs, builds, secures, and ships real systems, not demos. A multi-agent AI platform with live users, a sports product in production, and an iOS app in beta. Below is the work, with the architecture you can dig into.
Shipped systems across agentic AI, full-stack product, and mobile. Each one designed, built, and deployed end to end by me.
A production AI platform that runs a person's day. A routing layer sends each request to the right one of 14 specialized agents, which reason over the user's documents and live tools and draft every action for approval before it runs. Multi-tenant cloud, RAG, and a full DevSecOps pipeline, all built by me. Architecture below.
A full-stack sports training platform: four connected roles, 262 drills across 13 sports, with a drill engine that renders animated SVG diagrams from structured data. Web plus iPhone.
An athlete-path engine that retunes the whole program around the user across seven paths. Shipped to TestFlight with full account lifecycle, an App Store compliant paywall, and media handling.
A server-side pipeline that turns a structured brief into a finished branded vertical video: it plans the shots, renders them with ffmpeg, burns in captions, adds an ElevenLabs voiceover, and assembles the cut. Re-roll any single shot and it reassembles automatically.
A user talks to APEX; a routing layer sends the request to the right specialized agent; the agent reasons over the user's documents and live tools and drafts any action for approval before it runs. I own the whole system: the orchestration, the RAG pipeline, the connectors, the cloud, the security, and the reliability.
A certainty-gated router dispatches to 14 agents, with a strategic meta-agent that weighs the higher-leverage move. Distinct per-agent personas and server-side voices.
Tool and function calling across Gmail, Calendar, and Slack. The model drafts every action; nothing runs without a human yes. Automation with a real safety gate.
PDF, Excel, and text intake into a per-user knowledge base the agents reason over, so answers cite the user's real world, not generic guesses.
Node.js backend on Supabase with per-user runtime isolation, AES-256-GCM at-rest encryption, encrypted OAuth tokens, and self-serve password reset.
GitHub Actions CI/CD with Trivy, Semgrep, gitleaks; per-request CSP nonces, SRI, SSRF and prompt-injection guards; a CASA Tier 2 review; actions pinned to commit SHAs.
A 4-state presence machine, health checks and keep-warm to kill cold-start gaps, voice retry/cache, prompt caching for latency and cost, and on-screen latency/throughput telemetry.
I am an AI and software engineer and a U.S. Marine Corps infantry veteran. I learn a domain by building in it, and I take a thing from blank page to deployed and keep it healthy after launch. APEX exists because I wanted to prove that one person could design, build, secure, and operate a real multi-agent AI system. I work daily in Claude Code, Cursor, and Copilot, and I am completing a B.S. in Information Systems and Cyber Security with a 4.0 GPA.
Ownership, urgency, and finding a way when the path is not paved are not slogans to me. They are how I operate.
I am open to AI / software engineering roles. The fastest way to judge me is to read the architecture above and the projects.