MITO AI
Todas las habilidades, cualificaciones y experiencia relevantes que necesitará un candidato seleccionado se enumeran en la siguiente descripción.Location: Madrid (hybrid)About MITO AIMITO AI is a collaborative, AI-native platform reinventing how films, commercials, and music videos are made. We are building the operating system for a $300B+ global video production industry as it shifts to AI-native workflows.Headquartered between San Francisco (team of 2) and Madrid (team of 14), MITO combines state-of-the-art AI models for image, video, and audio with professional-grade editing tools in a multiplayer, browser-based canvas. Creators and teams can also bring ideas to life by directing an AI agent that generates scripts, scenes and edits in real time.MITO was founded by Iñaki Berenguer (Master MIT, PhD Cambridge, 5x founder and CEO, founded social photo startup Pixable acquired by SingTel, founded of CoverWallet $300M exit in 4 years, founded AI infrastructure company iPronics, which has raised $50M) & Danny Saltaren (award-winning product designer at 2 tech unicorns, National Design Award recipient) and Arantxa Barcia (Art Director).We are backed by Lightspeed Venture Partners and investors including Kibo, Kfund, Sequoia and a16z scouts, LifeX, Everywhere, 5 unicorn founders, and execs from Github and Roblox.Role OverviewThis role owns the data backbone that makes that possible.You will design and scale the event, asset, and metadata architecture that powers creative collaboration, AI orchestration, and real-time editing. This is not generic CRUD backend work — this is building the foundation of a next-generation creative system.What You Will OwnData ArchitectureDesign ingestion and processing pipelines for user events, AI outputs, asset metadata, and collaboration signalsArchitect event-driven systems that support real-time canvas interactions and timeline editsDefine schemas for scenes, assets, storyboards, prompts, model outputs, and versioningEnsure traceability across multi-model AI workflowsInfrastructure & PerformanceBuild scalable pipelines for high-volume creative assets (images, video, audio, embeddings)Optimize storage, indexing, and retrieval across structured and unstructured dataMaintain performance across collaborative sessions and multi-user editingBalance cost efficiency with low latencyObservability & ReliabilityImplement monitoring and logging across AI calls, orchestration layers, and asset pipelinesEnsure reproducibility and lineage of generated outputsDesign systems that tolerate model variability and partial failuresCollaborationWork closely with AI engineers to expose structured data for orchestration and retrievalPartner with frontend engineers to optimize real-time synchronizationSupport product in defining metrics across activation, engagement, and creative output qualityTechnical StackTypeScript - Node. xiphteb js - PythonPostgres - ClickHouse - Object Storage (S3-compatible)Kafka or event streaming systemsVector databasesCloud-native deployment (Docker, CI/CD)Experience with media processing pipelines is a strong plus.Who We Are Looking For5+ years building distributed backend or data infrastructureExperience with event-driven architectures and high-throughput systemsStrong schema design and data modeling intuitionComfortable working with unstructured and semi-structured dataStartup mindset: pragmatic, fast, accountableCurious about AI-native systems and creative workflowsWhat Success Looks LikeCreative workflows feel instant and reliableAI outputs are traceable and reproducibleCollaboration works in real time without breakingData architecture scales as usage growsEngineering moves faster because the foundations are solid