Projects
Engineering case studies focused on architecture depth, delivery context, and impact.
The portfolio favors clear framing around problem, role, implementation approach, and technical leverage.
Local-first developer tooling
mcp-test-impactMCP Test Impact Analysis System
A local-first engineering tool that analyzes code changes and predicts likely test impact without requiring external AI infrastructure.
Challenge
Reduce unnecessary test execution while keeping engineering data local, secure, and operationally simple.
Solution
Designed an MCP-oriented workflow that inspects changes, maps likely affected test surfaces, and integrates with developer tooling and qTest-aligned processes.
Impact
Demonstrates architecture thinking, CI efficiency awareness, and a privacy-conscious approach to AI-assisted engineering automation.
TypeScriptMCPLocal-first designqTest integrationDeveloper tooling
Workflow and documentation system
spec-driven-engineeringSpec-Driven Engineering Framework
A structured engineering workflow that turns specification artifacts into implementation guidance, architecture alignment, and project consistency.
Challenge
Create a reproducible path from requirements to delivery without losing technical rigor or documentation quality.
Solution
Built a specification-centric process that supports architecture notes, implementation guidance, agent collaboration, and documentation automation.
Impact
Shows process design maturity and a strong point of view on how engineering teams can improve quality through better artifacts.
Structured docsAI workflowsArchitecture diagramsDocumentation automationProcess design
AI platform experimentation
local-llm-platformLocal LLM Developer Platform
An experimental platform for integrating local LLMs into day-to-day software development without sending sensitive project context to external services.
Challenge
Balance privacy, speed, and developer experience when bringing AI assistance into real engineering workflows.
Solution
Integrated local inference, editor tooling, and coding-assistant patterns into a practical platform for secure experimentation.
Impact
Highlights AI infrastructure literacy, privacy-aware workflow design, and an execution-focused approach to developer productivity.
OllamaVS CodeLocal inferenceAgent toolingPrivacy-aware workflows
Enterprise engineering systems
platform-infra-toolingPlatform, Infrastructure, and Developer Tooling Work
A grouped portfolio area covering backend platforms, cloud-native infrastructure, automation, and developer-facing tooling across enterprise contexts.
Challenge
Support delivery at scale across backend services, infrastructure layers, and engineering operations.
Solution
Contributed architecture direction, service integration patterns, automation scripts, and operational platform improvements.
Impact
Reinforces breadth across backend, Kubernetes environments, automation, and technical leadership under real delivery constraints.
Backend platformsKubernetesRancherAutomationService integration