About Me
Defense software engineering leader with 8 years of full-stack development and operational test experience, all with an active TS/SCI clearance. Led tri-service evaluation of the DoD's first Joint Cyber C2 platform, translating field requirements from Air Force, Army, and Navy stakeholders into test architectures that resolved 6 critical deficiencies. At the AF-MIT AI Accelerator, deployed a production GPT-4 pipeline that replaced manual reporting for USAF operations. Currently building production C#/.NET and Python applications at DS2 for DoD clients.
My technical work ranges from GPU-accelerated computer vision systems for real-time airfield damage detection to full-stack React and Svelte web applications to LLM-powered operational tooling. I'm comfortable across the stack and across domains, from Python data pipelines and deep learning models to C#/.NET desktop applications and system architecture.
Quick Facts
- ▸ Currently: Software Engineer at DS2, Niceville FL
- ▸ Clearance: Active Top Secret / SCI
- ▸ Education: MS Electrical Engineering, AFIT
- ▸ Education: BS Electrical Engineering, University of Idaho
- ▸ Former: USAF Officer, AI Research Fellow at MIT
- ▸ Recognition: Stanford AI Professional Certificate, IEEE Published
Work History
Software Engineer, Government Services
DS2 / Dynamic Software Solutions
- ▸ Building production C#/.NET applications for DoD clients across the full stack: backend service architecture, REST API integration, and CI/CD-gated testing
- ▸ Developed a GPU-accelerated Python computer vision system for real-time airfield damage detection using YOLOv8x, SAHI sliced inference, GStreamer RTSP ingestion, BotSort tracking, and KLV/MISB-0601 metadata parsing
- ▸ Docker-containerized the companion FastAPI test harness with regression tests across single-image, RTSP video, and batch modes, aiding military operators to assess airfield damage in the field at real time
AI Applications Research Fellow
Air Force–MIT AI Accelerator
- ▸ Deployed production GPT-4 pipelines in Python to automate USAF operational reporting, cutting 800+ hours/year of manual work; pipelines ran in a live USAF test environment with non-technical operators as primary users
- ▸ Built the full stack: data ingestion from structured operational feeds, LLM integration with OpenAI API and LangChain, multi-step agent workflows for summarization and decision support, and a Streamlit front end for non-technical operators
- ▸ Pushed AI/LLM tool adoption across the fellowship, prototyping agentic workflows and presenting findings to Air Force leadership
Test Engineering Deputy / Operational Test Analyst
Air Force Operational Test & Evaluation Center
- ▸ Led the one-year tri-service evaluation of the DoD's first Joint Cyber C2 platform: gathered requirements from Air Force, Army, and Navy field operators, translated them into test architecture, identified 6 critical deficiencies, and tracked resolution across service stakeholders
- ▸ Directed AI-enabled operational test for 7 Joint Major Defense Acquisition Programs, validating C2, AI, and autonomous system capabilities against national security mission requirements
- ▸ Designed HIL/SIL operational test for defense weapons systems; managed data collection plans and KPP/KSA performance metrics across 47 flight test events
- ▸ Ran cyber vulnerability assessments for a cloud-based C2 program, accelerating the test schedule by 15%
- ▸ Led a 63-member, 10-organization working group synchronizing operators, developers, and integration/test/training teams across 2 joint C2 programs
Engineer & Deputy Program Manager
Air Force Research Laboratory
- ▸ Managed a 34-person multidisciplinary engineering team on a directed energy research program, coordinating hardware and software subsystem integration with industry partners across the full program lifecycle
- ▸ Designed a scalable pulsed laser system exceeding energy targets by 50% through optimized thermal management
- ▸ Prevented a 6-month schedule slip through early risk-reduction analysis
Projects
A selection of personal and open-source work
WarBot
End-to-end GPT-4 pipeline for USAF operator use: RAG-adjacent integration with structured operational data, multi-step agent workflows for summarization and reporting, and a Streamlit front end for non-technical users. Deployed to a live USAF operational test environment, cutting 800+ hours/year of manual work.
Damage Detection Algorithm (DDA)
Real-time airfield damage detection from aerial ISR video using YOLOv8x, SAHI sliced inference, GStreamer RTSP ingestion, BotSort tracking, and KLV/MISB-0601 metadata parsing. Docker-containerized with a CI/CD FastAPI test harness for repeatable regression testing across single-image, RTSP video, and batch modes.
Other Projects
Computer Vision Pipeline with Synthetic Data
Synthetic imagery pipeline in Python, TensorFlow, and Blender to train a UNet segmentation model for automated aircraft surface inspection. This approach removes the need for expensive real-world annotation data collection by training entirely on procedurally generated images.
PointSpire
Full-stack task and project management application with a REST API backend, JWT authentication, and real-time UI updates. Developed collaboratively using Agile/Scrum practices with a structured MVC architecture.
Skills & Expertise
Programming Languages
Frameworks & Libraries
Tools & Platforms
Domains & Concepts
Certifications & Recognition
Get in Touch
Open to new opportunities in software engineering, defense tech, and AI applications. Reach out directly. I'm always happy to talk.
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