AI Platform Engineer & Product Builder focused on building real-world AI systems.
I design and build systems that combine machine learning, LLMs, and distributed architectures to solve complex business problems.
- Design AI-powered systems and platforms
- Build multi-agent architectures and LLM orchestration layers
- Develop machine learning systems for real-world operations
- Create AI-native products and SaaS platforms
Revisiting and transforming a system I originally worked on 10+ years ago — now powered by AI.
- Migrating legacy mobile platform (Xamarin → .NET for Android)
- Designing ML-driven recommendation system (product, quantity, cross-sell)
- Integrating with Microsoft Fabric
- Building feedback loops for continuous model improvement
A distributed AI system to unify finance, operations, and automation via conversational interfaces.
- Multi-agent architecture (Finance, Operations, Knowledge, Automation)
- LLM orchestration with dynamic tool execution
- Workflow automation (Temporal, event-driven systems)
- Observability and execution tracing
Multi-tenant AI system to process financial documents using LLMs and multimodal pipelines.
- PDF, image, and CSV processing
- Document classification and structured extraction
- Queue-based scalable architecture
- Closed-loop prompt optimization
- Financial analytics and forecasting
Reusable ML platform for demand prediction and cross-sell strategies.
- Multi-model pipeline (LightGBM, XGBoost, similarity models)
- MLflow model lifecycle management
- Automated retraining pipelines
- Baseline-gated production validation
AI / ML
- Machine Learning (LightGBM, XGBoost)
- LLMs (OpenAI, Anthropic, Google)
- RAG & AI pipelines
- Multi-agent systems
Backend
- Node.js, TypeScript, Python
- FastAPI, Express
- PostgreSQL, Redis
Infra
- Docker, Railway, AWS
- Temporal, Airflow
- Observability (Prometheus, Grafana)
I don’t just use AI — I design the systems that make AI work in production.
Check my AI systems portfolio: https://alvaromunozmx.github.io/alvaromunozmx/