Oscar López Martínez

Robust enterprise foundations. High-impact AI solutions.

Senior software engineer with proven backend architecture experience (.NET) and modern ecosystem proficiency (TypeScript, React, Next.js), designing and implementing intelligent systems for business leaders and technical teams.

Explore Projects Get in Touch

Evidence & Track Record

Featured Reference Architectures

Problem → AI Solution → Impact

RAG & Document IntelligenceReference Architecture

DevBrain — Document Intelligence Platform

THE CHALLENGE

Organizations lose critical hours manually searching, extracting, and synthesizing information across disparate technical documents, PDFs, and codebase files.

TECHNICAL ARCHITECTURE

Production-grade RAG platform featuring hybrid semantic vector search with pgvector, multi-agent reasoning via LangGraph, and streaming responses with citation verification.

PythonFastAPINext.jsTypeScriptPostgreSQLpgvectorLangGraphDocker

View Code (GitHub) ↗

Multimodal AI & Rapid PrototypingSystem PoC

VerifyGo — AI Hackathon App

THE CHALLENGE

Fast-paced travel and event verification workflows require immediate multimodal validation of passes, tickets, and identity documents without human latency.

TECHNICAL ARCHITECTURE

Full-stack application engineered for the Talent Arena Hackathon using Google Gemini GenAI SDK for zero-shot document classification and fluid motion UI.

React 19TypeScriptGoogle Gemini APIViteTailwind CSSMotion

View Code (GitHub) ↗Live Demo ↗

Enterprise Backend & Data AccessReference Architecture

Enterprise .NET Core Web API

THE CHALLENGE

Enterprise microservices requiring maximum throughput and deterministic latency often suffer when bound to heavy ORM layers and unoptimized SQL execution.

TECHNICAL ARCHITECTURE

Production-ready ASP.NET Core Web API demonstrating Clean Architecture, ADO.NET direct SQL execution for optimal performance, and containerized Docker setup.

.NET CoreC#ADO.NETSQL ServerSwaggerDocker

View Code (GitHub) ↗

Trajectory & Evolution

The Bridge: From Enterprise Rigor to Applied AI

My background is rooted in the .NET / C# enterprise ecosystem. That gave me a profound understanding of what matters when systems scale: strict typing, transactions, resilient fault handling, clean architecture layers, and long-term maintainability.

My natural curiosity led me to adopt the modern web stack with TypeScript, React, and Next.js, merging that disciplined backend engineering with the speed, responsiveness, and polish of contemporary web products.

Today, I leverage that exact foundation to engineer applied AI systems: from autonomous agents and semantic retrieval pipelines to deterministic LLM workflows integrated safely into core business logic.

1. ENTERPRISE FOUNDATIONS.NET / C# / SQL
2. MODERN ECOSYSTEMTypeScript / React / Next.js
3. APPLIED AI ENGINEERINGRAG / Agents / LLM Ops

→ An engineering mindset that bridges deep systems architecture and business ROI.

Work Philosophy

Three Core Pillars of Value

Analytical Rigor & Enterprise Foundations

Architecting for edge cases, security, and long-term maintainability. Zero shortcuts or technical debt that compromise future product stability.

Accelerated Adaptation

Relentless technical curiosity paired with a disciplined method to assimilate emerging technologies and deliver production value from day one.

Pragmatic Business AI

AI is an engineering multiplier for operational efficiency and measurable business ROI, not a speculative marketing ornament.

Direct Contact

Let's discuss a technical or business challenge

Open to high-impact projects, technical advisory, and engineering leadership roles focused on applied AI and resilient systems architecture.

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