Chief Engineer focused on autonomous systems, agentic AI, and complex software-hardware systems.
I build and lead multidisciplinary engineering efforts spanning autonomy, AI-enabled software, robotics, full-stack applications, and human-machine teaming.
Previously Chief Engineer at L3Harris leading collaborative autonomy R&D. Currently Founder & Technical Lead at Praxis Defense and Perti Laboratories. This Github is where I work on persona projects and share some snapshots of work going on across my various ventures
A locally hosted AI chief-of-staff and orchestration platform designed around persistent context, multi-agent execution, and tool-enabled workflows.
What makes it interesting
- Persistent memory and structured operational context across multiple domains
- Multi-agent orchestration with explicit planning, approval, and execution flows
- Tool-enabled agents with scoped permissions and human approval gates
- Scheduled and background workflows with queue-based execution
- Codex integration for delegated software-engineering tasks
- FastAPI + React/Vite + PostgreSQL architecture
My role I designed the system architecture and built the platform end-to-end, using agentic AI engineering workflows to accelerate implementation while retaining ownership of architecture, integration, testing, and technical decisions.
Demo The system runs against real personal and work context, so I do not maintain a public live instance. Reach out if you'd like a walkthrough.
Perti Laboratories — proprietary commercial software https://app.aace.perti.io/
AAce is a multi-tenant customer journey platform that combines deterministic workflow orchestration with controlled AI interactions to manage customer engagement from initial lead through conversion and ongoing customer relationships. AAce is designed to be your company's best employee, wokring 24/7 whereve your customers are. It answers a simple question - if your customers have one journey with your company, why doesn't your company manage one journey for your customers?
Technical highlights
- Visual journey engine combining deterministic workflow logic with AI-enabled nodes
- Persistent contact, opportunity, consent, conversation, and journey state
- Multi-tenant SaaS architecture with tenant-isolated configuration and data
- LLM-powered conversations integrated into controlled business workflows
- Embeddable web experiences and multi-channel customer engagement
- Full-stack architecture using React, FastAPI, PostgreSQL, APIs, and containerized infrastructure
My role I designed the product and system architecture and lead full-stack development, using agentic AI engineering workflows to independently build and iterate on the production platform.
Architecture & Demo The production repository is private while AAce is under active commercial deployment. Our site has a brief public demonstration that gives you a peak at what AAce can do, its pretty barebones though so just reach out and I'll show you the whole thing. Reach out if you'd like a deeper product or technical walkthrough.
Perti Laboratories — active R&D
Ophi is a human-machine teaming architecture exploring how physiological and behavioral signals from wearable sensors can become actionable inputs to autonomous systems. Essentially designing the human body's API for integrating with an autonomous swarm.
The system is designed around a hardware-agnostic physiological data layer, edge processing and integration services, and higher-level tools for experimentation, operator modeling, and human-machine interaction. There are two active models:
(1) FLECKS - The Field Leader Electromyographic Communications KitS This allows a human to communicate intent to robotic systems using the same hand and arm signalsthey already use to communicate with their human teammates.
(2) VITALS - Vital-sign Intelligence for Triage, Assessment, and Life Support VITALS take a combination of physiological signals from commercial wearables to create a state variable for human health. This is similarly corrrelated with desired autonomous behaviors and will eventually become context that the swarm can reason about.
Technical focus
- Multimodal physiological and wearable sensor integration
- Hardware-agnostic data ingestion and normalization
- Real-time / edge processing architectures
- Human-state estimation and machine-learning pipelines
- Interfaces between physiological state and autonomous systems
- Simulation and experimentation with autonomous platforms
- Modular architecture spanning sensing, models, edge services, and applications
My role I conceived the system architecture and lead its technical development, combining my background in autonomy, systems engineering, neuroengineering, wearable sensing, and human-machine teaming.
Current status Ophi is under active R&D. The repository contains substantial architecture and systems-design work; the Ophi Console application is still in development. Reach out if you'd like to discuss the architecture or research direction.
Python · FastAPI · React · PostgreSQL · Docker · LLM Systems · Agentic AI · Autonomy · Robotics · Sensor Fusion · MBSE