Gabo Esquivel - AI EngineerArtificial Intelligence Experience

With over 15 years in full-stack software engineering, I help organizations turn initial ideas into market-ready software products, ensuring concepts reach their full potential. I work as a product engineer, bridging technical execution with user experience and business strategy.

AI is reshaping how we live, work, and interact with technology. The past few years, I’ve focused on building AI applications that prioritize user experience—moving beyond static interfaces toward systems where voice, chat, search, and action converge into more natural, dynamic interactions.

Wizard World: NFT Generation (2023)

Built during the Flow Hackathon, Wizard World connected OpenAI’s LLMs with the Flow blockchain. The app enabled users to generate AI images and mint them as NFTs—bridging creative expression with on-chain ownership.

Masterbots: Specialized AI Bots (2023)

Masterbots.ai delivers domain-specific chatbots optimized for complex tasks and long-context interactions. By using advanced prompt engineering techniques, we improve response quality and create more capable, user-friendly assistants. I contributed by designing the platform’s architecture, integrating Next.js, the AI SDK, and Supabase with pgvector to support scalable, context-aware interactions.

Bitlauncher: AI Crypto Launchpad (2023)

Bitlauncher is an AI crypto launchpad giving users early access to promising AI startups via token sales and batch auctions. We implemented a fair price discovery mechanism and recently added a chatbot powered by RAG and the experimental RSC AI SDK, enabling fast, conversational access to investment docs and platform data. I led the development and designed the full architecture, using Next.js, the AI SDK, and Supabase with pgvector to build a robust, scalable platform.

LegalAgent: AI for Legal Operations (2024)

At LegalAgent, I helped with the development of a mobile app featuring voice and text interfaces that transformed how their legal team accessed and understood internal documentation. By implementing a secure, retrieval-augmented generation (RAG) system we enabled lawyers to query contracts, memos, and regulatory docs in natural language. This project also involved developing a backend system to manage the system's prompts, allowing admins to adjust the assistant's behavior. Additionally, we integrated third-party systems like billing and case tracking APIs using advanced tools, resulting in a more responsive legal operation that accelerated knowledge access and reduced research friction.