// curriculum_vitae
Raul Vasquez
Machine Learning Engineer · AI Systems
// summary
Machine Learning Engineer with solid experience in AI, data engineering, and cloud computing. Specialized in designing, optimizing, and deploying scalable ML systems and full-stack applications. Builds advanced agent-based architectures and retrieval-augmented generation (RAG) systems with LangChain/LangGraph, integrating tool orchestration, persistent memory, and human-in-the-loop workflows.
// skills
AI Agents & Orchestration
RAG & Vector Search
MCP (Model Context Protocol)
Backend & Data
ML & Deep Learning
Frontend
Cloud & DevOps
Languages & Tools
// experience
Full-Stack Developer & AI Engineer
2025 – PresentW3bInnovation · Remote
- ›Designed and deployed intelligent-agent architectures with LangChain & LangGraph — agent workflows, tool orchestration, persistent memory (PostgreSQL checkpointer + store), and structured decision pipelines.
- ›Built multi-tenant RAG systems with pgvector and Ollama embeddings, improving factual consistency and traceability of conversational AI for enterprise clients.
- ›Implemented an MCP server (fastapi-mcp) exposing project, document, and RAG tools to external agents — with API-key authentication, scoped permissions, and request logging.
- ›Developed FastAPI services for LLM inference, authentication, session management, and agent lifecycle orchestration; designed a polymorphic RBAC system with resource-grant inheritance (organization → project → conversation).
- ›Built React + TailwindCSS + React Router v7 frontends with WebSocket streaming for real-time agent token responses, tool-use indicators, and human-in-the-loop interrupts.
Machine Learning Engineer
2022 – 2024Datyra · San Diego, USA
ML & Data Modeling
- ›Developed and deployed scalable ML systems with TensorFlow, PyTorch, Scikit-learn, and Keras: regression, classification, clustering.
- ›Fine-tuned vision-language and LLM models (X-CLIP, LLaMA) for object detection, semantic understanding, and domain-specific response generation.
- ›Built LLM-powered systems for automated reporting, structured data analysis, and conversational interfaces using prompt engineering and customized RAG pipelines.
Cloud & Data
- ›Managed PostgreSQL, MySQL, MongoDB; designed scalable architectures on AWS and Azure.
Automation & Deployment
- ›Designed automated training/validation/deployment pipelines (Python + Bash, CI/CD); deployed containerized apps via Docker and Kubernetes.
Software & Web
- ›Implemented GraphQL services in Go; integrated Stripe payments and referral systems; built secure RBAC authentication.
Productivity & Visualization
- ›Built dashboards and internal tools with Apache Superset, Mercury, and Retool; managed audience segmentation via Mailchimp.
// projects
This monorepo — Next.js 14 + FastAPI + LangGraph + pgvector. Live demos for streaming chat, RAG, and agent visualization. Provider-agnostic LLM (Ollama in dev, OpenAI in prod).
Python CLI agent with MCP tool integration, persistent memory (filesystem + PostgreSQL), configurable models (Ollama local + cloud), and thread management.
Chat platform on LangGraph + Chainlit + MCP. Uses AsyncPostgresSaver/Store, summarization / HITL / todo-list middleware, and multi-server MCP integration.
Client project (anonymized). FastAPI backend with LangGraph SDK; React Router v7 + Tailwind v4 frontend. Polymorphic RBAC, MCP server with API keys, conversation sharing, WebSocket token streaming.
// education
Master in Robotics
Universidad Tecnológica de la Mixteca
Bachelor in Mechatronics
Universidad Tecnológica de la Mixteca
// languages
- SpanishNative
- EnglishProficient
// certifications
- ✓Applied Data Science with Python Specialization (Mar 2022)
- ✓SQL and PostgreSQL: The Complete Developer's Guide (Feb 2022)
- ✓IBM Data Engineering Specialization (Feb 2022)
- ✓NoSQL, Big Data, and Spark Foundations Specialization (Apr 2022)
- ✓BI Foundations with SQL, ETL, and Data Warehousing Specialization (Apr 2022)
- ✓Python for Everybody Specialization (Feb 2022)