Senior Full-Stack & Azure Engineer • .NET + Angular/React • Cloud • Data • AI
I build reliable, scalable systems in Azure—then ship them with the discipline to make impact.

My purpose: discipline + continuous learning + pragmatic technology to lead by example and deliver measurable value.

Current focus: Building production Generative AI systems with Azure OpenAI—RAG pipelines, embeddings, vector search, content safety, and grounded chat. Integrating Python/Django with Azure AI services for intelligent backends.

Next milestone: AZ-104 (Azure Administrator) and AZ-305 (Azure Solutions Architect Expert) to design and operate enterprise-scale Azure architectures.

• FenecAI – Production Generative AI platform (.NET 8):
  GPT-4 Chat, RAG with Azure AI Search, Embeddings, DALL·E 3, Content Safety, Metrics, comprehensive API docs.
• Backend .NET Clean Architecture – Scalable API foundation with Azure integration.
• Blob Storage API – Enterprise file services on Azure Storage.
• Cosmos DB API – Optimized data patterns for Azure Cosmos DB.

I build systems that are observable, secure, and maintainable from day one—not technical debt disguised as MVPs.

Core:
C# • TypeScript • JavaScript • Python • SQL

Backend:
.NET 8/7 • ASP.NET Core • Minimal APIs • EF Core • Dapper • Django

Frontend:
Angular • React • RxJS • NgRx • AG Grid • Tailwind CSS

Azure Cloud:
App Service • Functions • Storage • Cosmos DB • Azure OpenAI • Azure AI Search • Azure AI Content Safety • Key Vault • App Configuration • Event Grid

AI & Data:
Azure OpenAI (GPT-4, Embeddings, DALL·E) • Vector Search • RAG • Prompt Engineering • Semantic Kernel

DevOps & Practices:
GitHub Actions • CI/CD • Docker • IaC (Bicep/ARM) • Clean Architecture • SOLID • CQRS • Observability • Security by Default

• GenAI in Production: Evaluation frameworks, content safety, grounding techniques, cost optimization, telemetry.
• Azure Architecture: Designing resilient, secure, enterprise-scale solutions (AZ-104/AZ-305 track).
• Vector Search & RAG: Embeddings strategy, chunking optimization, hybrid search, index quality.
• Python/Django + Azure AI: Building intelligent APIs, ML-driven features, backend automation.
• Developer Experience: APIs that teach, documentation that scales, guardrails that enable velocity.

Completed:
✅ Azure Fundamentals (AZ-900)
✅ Azure Developer Associate (AZ-204)
✅ Azure AI Engineer Associate (AI-102)
✅ Azure Data Fundamentals (DP-900)
✅ Azure AI Fundamentals (AI-900)

In Progress:
🎯 AZ-104 – Azure Administrator Associate
🎯 AZ-305 – Azure Solutions Architect Expert

Deep Dive Topics:

• Generative AI orchestration patterns
• Vector databases & semantic search
• Azure AI services integration
• Enterprise architecture patterns
• Python for Azure AI automation

"Excellence is a habit. I code with intention, learn with discipline, and ship with integrity."