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
