AI Systems Architect · Technical Leader · Full-stack Applications Developer

Technical leader with 20+ years architecting intelligent, cloud-native platforms that integrate applied AI, scalable infrastructure, and full-stack product systems. I specialize in embedding multi-agent orchestration, model alignment workflows, and generative pipelines into production environments—with a focus on performance, reliability, and long-term maintainability.

Currently building adaptive execution pipelines that continuously evaluate outputs, correct failures, and optimize behavior across successive runs. These systems use structured feedback signals and policy-driven guardrails to maintain safety, determinism, and operational trust.

Virtual Coach, Inc
Computer vision pipeline for youth sports analytics—integrating pose estimation, object tracking, and temporal action recognition to extract biomechanical metrics from video. LLM-powered analysis layer generates personalized coaching feedback, drill recommendations, and performance trend reports from structured movement data.

JAZU Labs: AI-Native Advertising Platform
Real-time bidding optimization engine with multi-armed bandit experimentation, creative variant analysis, and attribution-aware budget allocation. Combines behavioral signal processing with LLM-driven copy generation to enable continuous micro-segmentation, A/B sequencing, and cross-channel performance convergence at sub-second latency.

Self-Healing Agent Ecosystems
Multi-agent orchestration framework where specialized agents collaborate through file-based communication, enforce quality gates at each pipeline stage, and automatically refine their own instruction sets based on graded output analysis and post-mortem feedback loops.

EllyMUD: Modern Multi-User Dungeon
A TypeScript-based MUD engine featuring real-time multiplayer combat, spellcasting with mana management, and a 12-slot equipment system. Supports multiple connection protocols (Telnet, WebSocket, web client) with pluggable storage backends (JSON, SQLite, PostgreSQL). Includes an MCP server for AI integration, enabling virtual gameplay sessions and automated testing. Built with a multi-agent development pipeline—10+ specialized AI agents handle research, implementation, validation, and documentation with automated rollback and post-mortem analysis.

• Multi-agent LLM orchestration with real-time data pipelines and edge-triggered workflows
• Computer vision inference systems for real-time video analysis and biomechanical extraction
• Production-grade observability for distributed, latency-sensitive AI workloads
• Cloud-native platforms with infrastructure-as-code, container orchestration, and CI/CD automation

AI/ML: PyTorch · TorchVision · FlashAttention · CUDA · Conda · ONNX
Vision: OpenCV · MediaPipe · YOLOv8 · DeepSORT · MMPose
Backend: TypeScript · Node.js · Python · PostgreSQL · Redis
Infrastructure: Docker · Kubernetes · GitHub Actions · Terraform
Frontend: React · Vite · WebSockets

"The future of AI-assisted development isn't a smarter single agent. It's a well-orchestrated team of focused agents that learn from every run."