I'm a Senior Full-Stack & AI Engineer from Montevideo, Uruguay 🇺🇾 with 9+ years building production-grade applications across fintech, real-time platforms, and AI-powered systems. I specialize in bridging AI/ML capabilities with real-world products — from LLM orchestration and RAG pipelines to ML-driven risk detection and algorithmic trading systems powered by reinforcement learning.

const diego = {
  location: "Montevideo, Uruguay 🇺🇾",
  role: "Senior Full-Stack & AI Engineer",
  currentFocus: [
    "AI-Powered SaaS Products",
    "LLM Orchestration & RAG Pipelines",
    "ML Risk Detection & Fraud Prevention",
    "Algorithmic Trading with Reinforcement Learning"
  ],
  building: {
    now: "AI-driven proposal system with dynamic content generation @ iDelsoft",
    recent: "AI agent payment gateway (x402 protocol) @ Proxify",
    ongoing: "RL trading systems with PPO/SAC algorithms"
  },
  stack: ["Python", "TypeScript", "React", "Next.js", "FastAPI", "Node.js", "LangChain", "PyTorch"],
  motto: "I take AI models and turn them into products people actually use"
};

• LLM-integrated SaaS platforms with dynamic content generation and intelligent recommendations
• RAG pipelines with vector databases (pgvector), embedding optimization, and evaluation frameworks
• Agentic workflows with LangChain/LangGraph, tool/function calling, and structured outputs
• AI agent infrastructure — payment gateways and APIs designed for autonomous AI agent consumption
• Prompt engineering pipelines with template management and industry-specific context injection

• Real-time risk scoring engines using scikit-learn for behavioral pattern analysis and anomaly detection
• Feature engineering pipelines extracting signals from session data, transaction velocity, and device fingerprints
• Automated anomaly detection for identifying unusual patterns in high-throughput transactional systems
• Fraud prevention systems with statistical modeling and real-time alerting

• Reinforcement learning trading systems using PPO and SAC algorithms with PyTorch
• Multi-symbol automated trading with real-time market data processing and risk management
• Trading dashboards and APIs built with Flask/FastAPI for portfolio management and ML model evaluation
• Feature engineering with technical indicators (RSI, EMA, ATR) for predictive modeling

• Production-grade APIs with FastAPI, Node.js, JWT authentication, and rate limiting
• Event-driven microservices with WebSocket, Redis pub/sub, and real-time data processing
• React/Next.js applications with TypeScript, SSR, and modern component architecture
• CI/CD pipelines with Docker, automated testing, and monitoring/telemetry

• LLM orchestration with LangChain, LangGraph, and agentic workflows
• RAG pipeline architecture with vector databases and embedding optimization
• Prompt engineering and structured outputs (Pydantic) in production systems
• Reinforcement learning (PPO, SAC) for adaptive trading strategies
• ML risk detection and real-time anomaly detection systems

• 9+ years developing financial applications and trading systems
• Real-time market data processing and analysis at scale
• Algorithmic trading with Python, PyTorch, and machine learning
• Risk management and portfolio optimization with custom evaluation frameworks
• Payment processing infrastructure for fintech platforms

• High-throughput systems processing thousands of concurrent transactions with sub-200ms latency
• Scalable microservices with event-driven architecture and container orchestration
• Database optimization for time-series and vector data (PostgreSQL, pgvector, Redis)
• Monitoring & observability with LangSmith, automated evaluation pipelines

• JWT/OAuth 2.0 authentication with complex multi-tenant flows
• API security with tiered rate limiting, abuse detection, and fraud prevention
• Secure transaction processing for financial and payment systems
• Data privacy best practices for regulated industries