I am a technical systems and quality assurance professional based in the Greater Seattle area. My background combines software QA leadership with hands-on experience building, configuring, testing, troubleshooting, and improving GPU platforms, custom workstations, local AI environments, and supporting infrastructure.
I focus on understanding how complete systems behave, reproducing and isolating failures, identifying practical corrective actions, and confirming whether changes improve reliability. My approach combines technical investigation, structured testing, documentation, cross-functional communication, and continuous improvement.
📍Greater Seattle Area, Washington
Cyber Excavation grew from the same systems-based approach shown throughout this portfolio: understand how the system works, identify constraints, test real behavior, document the process, and refine the outcome.
In my technical projects, that means working through hardware, power, cooling, configuration, monitoring, reliability, and local AI experimentation.
In Cyber Excavation, that same method is applied to small-business workflows. I help identify where work is repetitive, unclear, or inefficient, then build practical AI-assisted systems with human review, documentation, and ongoing refinement.
Understand the System
Study how the full system actually behaves.
Identify Constraints
Find bottlenecks, risks, dependencies, and failure points.
Test & Validate
Test real behavior, confirm fixes, and improve reliability.
Document & Refine
Turn lessons into repeatable processes.
Functional and System Testing
Hardware Integration and Validation
GPU Infrastructure and Compute Platforms
IT Operations and Technical Troubleshooting
Failure Analysis and Root-Cause Investigation
Process Design and Technical Documentation
Local AI and Workload Evaluation
Founder, Cyber Excavation
Lead Software Quality Assurance, Nintendo
Builder of multi-GPU systems for mining, local AI and compute workloads
Experience in technical troubleshooting, system optimization, project coordination and structured problem-solving
Planned, built, operated, and optimized multi-GPU compute environments
Managed power, cooling, thermal behavior, monitoring and stability
Repurposed compute infrastructure for local AI experimentation
Led QA testing, issue tracking, and cross-functional coordination
Translated ambiguous technical problems into practical, repeatable workflows
Technical Judgment
Troubleshooting & Root-Cause Analysis
Documentation & Process Clarity
Systems Thinking
Continuous Learning & Improvement
Systems building, AI workflow design, local AI experimentation, performance tuning, practical automation, technical documentation, and continuous learning.
Confidentiality Note
Some client-facing work is intentionally described in general terms to protect confidentiality. Examples and details are anonymized, redacted, or omitted.