Recruiters & hiring teams
See the fit quickly, then inspect the evidence.
Begin with a concise candidate brief, employment history, and the AI and systems work that shows how I operate across disciplines.
Systems Integration · AI Solutions · Technical Operations
I turn unclear problems into systems people can actually use.
I work where people, process, hardware, software, and AI meet. I learn how the work really happens, define what success must look like, direct the build, and verify the result in the environment where it has to perform.
Current engineering stackC# / .NETPythonPowerShellJavaScript / TypeScriptSQL / SQLiteWindows + embedded systems
- 20+ yearscross-domain technical work
- Build to handoffdiscovery, delivery, validation, support
- Human accountableAI accelerates work; evidence accepts it
Start with what brought you here
Two clear paths into the same work.
Prospective clients & collaborators
Start with the problem or outcome you need.
Review representative systems, prototypes, and field deployments, or send a private request describing what needs to work better.
Where I add value
The connective work most projects cannot afford to miss.
I am most useful when the problem crosses organizational or technical boundaries and needs one person to hold the complete system in view.
Field discovery
Find the operating problem behind the reported symptom and turn frontline knowledge into actionable requirements.
Systems integration
Connect software, hardware, networks, data, operators, and support processes into one coherent solution.
AI-directed delivery
Use AI agents as bounded specialist collaborators, review their code and design choices, and retain architecture, correction, and acceptance authority.
Evidence-based acceptance
Distinguish a plausible demo from a result that has been built, exercised, installed, and understood at the right evidence layer.
Selected work
Different technologies. The same practical discipline.
These projects show how I move from an operating need to a working system, from field-deployed products to local AI infrastructure and research platforms.
Working research prototype
Wireless sensing · embedded + Windows
Pegasus Sense
Turned a complex wireless-sensing concept into a repeatable five-device research platform with live RF acquisition, visualization, recording, replay, and observable response to environmental change.
Shows: embedded integration, measurement integrity, research design, hardware-in-loop acceptance.
Installed + exercised
Local AI work framework
Pegasus Cerebral
Coordinates local models, bounded semi-agent roles, durable work, tools, operator decisions, and expandable modules in one recoverable environment.
Shows: AI platform architecture, small-model orchestration, human authority, modular growth.Installed + integrated
Continuity + governed operations
Pegasus Cortex
Preserves bounded project knowledge and task state, retrieves only what work needs, and exposes explicit typed operations without turning stored context into authority.
Shows: durable context, retrieval discipline, safe local operations, recovery design.
Playable prototype
AI-directed product development
Neural Commander
A deterministic strategy-game prototype used to turn hands-on playtesting into system behavior, architecture decisions, regression tests, and native runtime evidence.
Shows: product direction, complex-state modeling, UAT, AI-assisted engineering.
Built + field deployed
Connected field product
Cellular virtual-tour kiosks
Specified, assembled, programmed, installed, and supported three public kiosks that combined touch, video, cellular service, request capture, and battery-backed power.
Shows: end-to-end ownership, component sourcing, deployment, field support.Functional prototype
Connected e-ink signage
Persistent digital signage
Multiple e-ink display sizes with QR-ready content, LoRa, Bluetooth, Wi-Fi, external-power support, and confirmed remote updates.
Shows: embedded product design, Windows integration, low-power communication, failure-aware operation.Multi-site deployment
Distributed business software
Offline-capable retail platform
Built a multi-location transaction system that kept stores operating through connectivity interruptions and synchronized results back to central operations.
Shows: resilient workflows, custom peripherals, site integration, support.Controlled local research
Geometric / latent reasoning
Model-efficiency research
Converted paper-derived ideas into controlled local experiments with frozen baselines, matched comparisons, quality review, and promotion gates that can reject an attractive but weaker result.
Shows: experiment design, failure analysis, decision discipline.Work and opportunity
For teams that need someone to connect the problem, the technology, and the people using it.
I am available for employment conversations and selected project work. The strongest fit is an unclear or cross-disciplinary problem that needs practical discovery, technical direction, integration, and proof that the result works in the real environment.
AI systems and automation
Find the useful AI role, define the surrounding system, direct implementation, and evaluate the result with the people who will use it.
Systems integration and solutions
Join hardware, software, data, networks, and workflows into a system that can be operated and supported.
Workflow diagnosis and prototyping
Trace repeated friction to its cause, shape a practical solution, and turn the idea into something people can evaluate.
Technical operations and recovery
Diagnose problems that cross systems, improve reliability, and translate between technical teams and frontline work.
Capabilities + technology
Technical breadth, organized around the work it supports.
The value is not any one tool. It is the ability to move between the operating need, the system design, the implementation choices, and the evidence required to trust the result.
Strategy + discovery
- Frontline discovery
- Requirements engineering
- Workflow mapping
- Stakeholder translation
- Acceptance criteria
- Technical product direction
Systems + operations
- Systems integration
- Root-cause analysis
- Test engineering
- Programmable instrumentation
- Embedded systems
- Deployment + recovery
AI + data
- Local AI infrastructure
- AI agent systems
- Human-in-the-loop AI
- Model evaluation
- Context + knowledge systems
- Privacy + authority boundaries
Engineering tools
- C# + .NET
- PowerShell
- Python
- JavaScript + TypeScript
- Visual Basic + VBA
- SQL + SQLite
Verification
- Reference-based test review
- Python test-data analysis
- Hardware-in-loop testing
- Executable acceptance
- Diagnostics + fault isolation
- Failure and recovery design