Descripción de la oferta
Senior Full Stack Developer (Node.Js Focus) – Open‑Source AI PlatformAbout the ProjectWe are building a sophisticated, open‑source AI conversational platform that integrates multiple AI providers to deliver a rich, cutting‑edge user experience. We are looking for an experienced Senior Full Stack Developer to join our core team as a B2B partner.Setup & Work ArrangementContract: 100% B2B / Independent Contractor (You must be registered as an Autónomo or have a corporate entity in Spain).Location: Hybrid. We require availability to be on‑site at our Madrid office 2‑3 days per week for architectural alignment, team syncs, and workshops. The rest of the time is remote.Language: Fluent English is required.What You Will DoTake ownership of the backend components, building a sophisticated AI chat platform.Implement new AI provider integrations (OpenAI, Claude, etc.) and complex chat functionalities.Design and optimize database structures using MongoDB and PostgreSQL.Implement and maintain real‑time features using WebSocket connections.Ensure code quality through automated testing and participate in high‑standard code reviews.Deploy and maintain containerized applications using Docker.Core Technical Stack (Required)Backend (Primary Focus):- Node.Js (v18+) with Express.Js framework.- Databases: MongoDB (with Mongoose), PostgreSQL, Redis (for caching & session management).- RESTful API design, JWT, and session‑based authentication.Frontend:- React.Js (v18+) with functional components and hooks.- TypeScript for type‑safe development.- Tooling & Styling: Vite, TailwindCSS, Radix UI / Headless UI.- State & Data: Tanstack Query (React Query), modern React state patterns, React Router.DevOps & Tools:- Docker & Docker Compose.- Git advanced workflows, ESLint, Prettier.- Environment configuration and secrets management.Nice‑to‑Haves (Bonus Points)- Hands‑on experience with OpenAI API, Anthropic Claude, or similar LLM APIs.- Understanding of prompt engineering and AI model integration.- Experience with the LangChain framework.- RAG (Retrieval‑Augmented Generation) implementation experience.#J-18808-Ljbffr
