I work at the intersection of AI systems, architecture, governance, and business execution.

My focus is turning probabilistic AI into predictable, auditable, decision-ready systems through:

• LLM and RAG architectures designed for production
• Reliability and observability for GenAI environments
• Governance, traceability, and risk control
• Cost-aware technical decisions with business visibility
• System integration that connects AI to real operations

Today, my work is especially centered on production-grade AI infrastructure, where reliability matters more than hype.

• Designing and operationalizing LLM / RAG systems
• Improving retrieval quality and reducing hallucination risk
• Building evaluation pipelines for higher-trust AI outputs
• Connecting Python / FastAPI AI services to business workflows
• Structuring AI initiatives with governance, monitoring, and measurable impact

• AI-ENGINE-PLATFORM-MCP-First
  MCP-oriented architecture exploring extensible AI tooling, protocol-driven integrations, and developer-facing interfaces.

• rag-documentation
  Documentation-focused RAG project covering retrieval pipelines, document ingestion, and context-aware AI workflows.

• Vibe-Coding-OS-Pure-Python-File-Based-Cache
  Cache and systems-oriented experimentation for AI-assisted workflows and performance-sensitive tooling.

• universal-project-hub
  Multi-project workspace concept focused on organization, collaboration, and developer productivity.

• webschema
  Component and design-system work centered on maintainability, reuse, and front-end consistency.

• linkly
  URL and analytics-oriented project demonstrating product thinking, backend structure, and operational use cases.

My background combines software, operations, product, and delivery:

• CTO at GLX Partners — architecture and governance for production-grade AI and GenAI systems
• AI Systems & Prompt Architect at Outlier AI — structured prompt systems, evaluation, and higher-trust LLM workflows
• Project management and consulting across AI, digital systems, automation, and business operations
• Frontend and web engineering experience in performance, conversion, and real business launches
• Experience supporting multi-brand operations, CRM workflows, SEO, funnels, and digital execution

This combination helps me connect: technical architecture ↔ operational execution ↔ business impact

AI / GenAI

• LLM systems
• RAG architecture
• Prompt systems
• Evaluation workflows
• Reliability for AI outputs

Software Engineering

• Python
• TypeScript / JavaScript
• FastAPI
• React
• Node.js
• API integration

Architecture & Delivery

• System design
• Technical strategy
• Governance
• Observability
• Process discipline
• Lean Six Sigma / Scrum / project execution

I’m especially interested in opportunities involving:

• AI platform engineering
• GenAI architecture
• LLM / RAG production systems
• AI governance and reliability
• Technical leadership across engineering and business
• High-trust AI products with measurable operational value