A1La información a continuación detalla los requisitos del puesto, la experiencia esperada del candidato y las cualificaciones correspondientes.There are over 5 billion users using basic applications today such email, notes, tasks that are not AI-native. Our mission is to build a proactive smart assistant for everyday users to bring intelligence to conversations, errands, organising and workflows, with minimal prompting.Our product focuses on achieving high reliability for long-running workflows, persistent context, and real-world task completion. The system must handle multi-step reasoning, interact with external tools, and remain reliable despite non-deterministic model behavior. Our objective is to help users complete tasks daily enjoyable with over ~90%* reduced time.RoleWe are looking for a Full Stack Engineer - AI Systems to build the product layer that turns these capabilities into usable, production-grade workflows. This includes designing how agents operate, fail, recover, and deliver consistent value to users.FocusBuild end-to-end product features across frontend, backend, and AI integrationsDesign agent workflows that handle planning, tool use, failure, and recovery across multiple steps.Integrate LLMs, memory, and external tools into systems that behave reliably under real-world conditionsDesign real-time AI interactions with streaming, partial results, and tight latency constraintsImprove system reliability, observability,



and fallback mechanismsCollaborate closely with ML, backend, and product teams to ship features end-to-endContinuously iterate based on real usage and failure modesIdeal ExperiencesStrong experience in full stack engineering (frontend + backend)Solid understanding of system design and API architectureExperience working with LLMs, RAG systems, or AI-powered applicationsAbility to handle ambiguity and make pragmatic engineering decisionsStrong ownership - able to take features from idea to productionComfort working in fast-moving environments with evolving requirementsOutcomesOwn and ship AI-native product features that move beyond chat into persistent, goal-driven workflowsDesign and deploy agent workflows that reliably complete multi-step tasks xcskxlj across tools and sessionsReduce latency and improve responsiveness of AI interactions while maintaining output qualityBuild robust fallback and recovery mechanisms for LLM and tool failures in production environmentsImprove the success rate and reliability of AI-driven workflows through iteration, evaluation, and monitoringEstablish patterns and abstractions for integrating LLMs, memory, and external tools into scalable product systemsContribute to a product experience where AI feels proactive, consistent, and dependable over timeTech StackNext.jsPythonNodeJsPytorchOpenAI / Anthropic / open-source LLMsSQL & noSQLKubernetesDocker#J-18808-Ljbffr

📌 Full Stack Engineer, AI systems (Madrid)
🏢 Talent
📍 Madrid