MITO AI brLocation: Madrid (hybrid) brAbout MITO AI brMITO AI is a collaborative, AI-native platform reinventing how films, commercials, and music videos are made. We are building the operating system for a $300 B+ global video production industry as it shifts to AI-native workflows. brHeadquartered 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. brMITO was founded by Iñaki Berenguer (Master MIT, Ph D Cambridge, 5x founder and CEO, founded social photo startup Pixable acquired by Sing Tel, founded of Cover Wallet $300 M exit in 4 years, founded AI infrastructure company i Pronics, which has raised $50 M) Danny Saltaren (award-winning product designer at 2 tech unicorns, National Design Award recipient) and Arantxa Barcia (Art Director). brWe are backed by Lightspeed Venture Partners and investors including Kibo, Kfund, Sequoia and a16z scouts, Life X, Everywhere, 5 unicorn founders, and execs from Github and Roblox. brRole Overview brThis role owns the data backbone that makes that possible. brYou 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. brWhat You Will Own brData Architecture brDesign ingestion and processing pipelines for user events, AI outputs, asset metadata, and collaboration signals brArchitect event-driven systems that support real-time canvas interactions and timeline edits brDefine schemas for scenes, assets, storyboards, prompts, model outputs, and versioning brEnsure traceability across multi-model AI workflows Infrastructure Performance brBuild scalable pipelines for high-volume creative assets (images, video, audio, embeddings) brOptimize storage, indexing, and retrieval across structured and unstructured data brMaintain performance across collaborative sessions and multi-user editing brBalance cost efficiency with low latency Observability Reliability brImplement monitoring and logging across AI calls, orchestration layers, and asset pipelines brEnsure reproducibility and lineage of generated outputs brDesign systems that tolerate model variability and partial failures Collaboration brWork closely with AI engineers to expose structured data for orchestration and retrieval brPartner with frontend engineers to optimize real-time synchronization brSupport product in defining metrics across activation, engagement, and creative output quality Technical Stack brType Script • Node.js • Python brPostgres • Click House • Object Storage (S3-compatible) brKafka or event streaming systems brVector databases brCloud-native deployment (Docker, CI/CD) Experience with media processing pipelines is a strong plus. brWho We Are Looking For br5+ years building distributed backend or data infrastructure brExperience with event-driven architectures and high-throughput systems brStrong schema design and data modeling intuition brComfortable working with unstructured and semi-structured data brStartup mindset: pragmatic, fast, accountable brCurious about AI-native systems and creative workflows What Success Looks Like brCreative workflows feel instant and reliable brAI outputs are traceable and reproducible brCollaboration works in real time without breaking brData architecture scales as usage grows brEngineering moves faster because the foundations are solid