Lázaro Gómez Vitolo
AI & Robotics Developer | Python • Node.js • AWS
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AI & Robotics Developer | Python • Node.js • AWS
Download CV Download Cover LetterAI & Robotics Developer with hands-on experience building projects in Python, AWS, Generative AI, Computer Vision, and automation. I enjoy developing solutions that combine software, artificial intelligence, and robotics to solve real-world problems.
My work focuses on AI-powered applications, cloud technologies, automation systems, and continuous learning through practical projects. I actively build and share projects involving AWS services, AI models, computer vision, and software development best practices.
Technical skills include Python, AWS, Node.js, React, Git/GitHub, Robotics, Artificial Intelligence, and Cloud Computing.
Currently interested in Junior AI Developer, Python Developer, Automation Engineer, and Robotics opportunities where I can contribute, learn, and grow while building impactful technology.
In programming I managed to understand the math of percentages and averages, which helped me to solve problems with quantities.
Courses: Mathematics and Introduction to Computer Science.
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“Never. Never give up. I’d have to be dead or completely incapacitated.” — Elon Musk
Practical Generative AI examples on AWS — chatbot and RAG system built with Amazon Bedrock, Anthropic Claude, and Python.
View on GitHubProject focused on integrating artificial intelligence with Mercado Libre to automate tasks, optimize listings and improve product management within the e-commerce ecosystem through intelligent tools and automated data processing.
View on GitHubRobot Vision Dashboard is a cloud-based prototype for monitoring AI-powered robotic vision systems. It displays real-time metrics, simulated camera feeds, and object detection data through an intuitive dashboard, providing a foundation for integrating live telemetry, computer vision, and cloud AI services.
View on GitHubA project focused on making the Copilot AI assistant more user-friendly and accessible.
View on GitHubA clean, opinionated Python starter kit that demonstrates core Claude API patterns: system prompts, conversation history management, streaming responses, function calling, and a ReAct-style agent loop with working tool integrations. Designed as a practical reference for developers getting started with Anthropic's API, built after completing the official Anthropic Academy course.
View on GitHubA TypeScript implementation of an MCP (Model Context Protocol) client that connects to a tool-serving MCP server and bridges its tools into a Claude-powered conversation. The client discovers available tools over a stdio transport, converts them into Claude-compatible tool definitions, and runs an agent loop — letting Claude decide when to call a tool, executing it via the protocol, and feeding results back until it produces a final answer. Includes a minimal example server exposing two demo tools, plus an architecture diagram illustrating the request flow between user, client, Claude, and server. Built as a follow-up to claude-api-starter, applying concepts from Anthropic Academy's "Introduction to Model Context Protocol" course to the client side of the protocol.
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