Senior Full-Stack & Azure AI Engineer • .NET + Angular/React • Cloud • Data • GenAI 12+ years shipping enterprise systems. Most recently: GenAI features in production at Hitachi Solutions (RAG, embeddings, multi-LLM) — now building my own AI products end to end on Azure.

My purpose: discipline + continuous learning + pragmatic technology. Ship something small, learn fast, iterate.

• Tyto — Document intelligence platform. Upload a document, extract structured data with Azure Document Intelligence + LLMs, persist it, and see per-field confidence and provenance. Angular 21 · .NET 10 · Azure SQL · Azure AD. Production-grade API: unit-of-work per request, RFC 7807 errors, rate limiting, Serilog + OpenTelemetry, encrypted secrets, full test suite. MVP launching this month.
• @alonsoegm/ui — Angular 21 component library: 16 tree-shakable entry points, layered design tokens, Tailwind v4 preset, signal-based APIs. Published to GitHub Packages via tag-triggered CI.
• Next up: a configurable GenAI workspace that adapts RAG-grounded generation to different business workflows — not just one use case.

Why these three: Microsoft's 2026 certification wave moved the Azure credentials toward agents and AI-native development. I hold AI-102 and AZ-204; AI-103 and AI-200 are their direct successors (agents on AI Foundry, AI workloads on Azure), and DP-800 brings vector search and RAG inside the SQL engine — exactly the stack Tyto runs on.

At Hitachi Solutions (innovation team, 2024–2026) I built GenAI features for TurboRFP, an internal RAG application in daily use by presales teams: reworked the embeddings pipeline, added semantic and vector search, and shipped multi-LLM support with per-user model selection. In parallel, I developed complex Angular functionality for an enterprise data-integration platform — including an analytics API redesign that cut response times by roughly 60%.

• FenecAI — .NET 8 Generative AI platform: GPT-4 chat, RAG with Azure AI Search, embeddings, DALL·E 3, Content Safety, metrics, full API docs.
• Backend .NET Clean Architecture — Scalable API foundation with Azure integration.

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 10/8 • ASP.NET Core Web API • EF Core • Django REST Framework • FluentValidation • Mapster

Frontend: Angular 17–21 (signals, standalone) • React • RxJS • NgRx • AG Grid • Tailwind CSS v4 • Vitest • Storybook • Cypress

Azure Cloud: App Service • Functions • Azure SQL • Storage • Cosmos DB • Key Vault • Service Bus • Application Insights

AI: Azure OpenAI (chat, streaming, embeddings) • RAG • Vector & semantic search • Azure AI Search • Document Intelligence • Content Safety • Prompt engineering • Semantic Kernel

DevOps & Practices: GitHub Actions • Azure DevOps • CI/CD • Docker • Clean Architecture • SOLID • OpenTelemetry/Serilog • Feature flags • Security by default

• Shipping Tyto to production: deployment, telemetry, cost control, and a public demo.
• AI agents on Azure AI Foundry: the AI-103 track — agent orchestration, evaluation, function calling.
• RAG quality: embeddings strategy, chunking, hybrid search, grounding evaluation.
• AI in the database: vector types and RAG workflows in T-SQL (DP-800 track).