> Markdown version of [/jobs/ext/3359780-senior-data-engineer-mosaic-ai](https://www.wearedevelopers.com/jobs/ext/3359780-senior-data-engineer-mosaic-ai). Every page supports `.md` or `Accept: text/markdown`. Links point to the HTML versions so they work for humans too. Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Senior Data Engineer (MOSAIC AI) - **Company:** Tecdata Engineering - **Location:** Madrid, Spain - **Contract:** Apprenticeship - **Skills:** Artificial Intelligence, Python (Programming Language), Machine Learning, Tensorflow, Search Technologies, Pytorch, Machine Learning Operations, Databricks - **Published:** September 21, 2026 - **Apply:** https://www.indeed.com/viewjob?jk=9780d43fcb50f1fd ## About the Role * Amplios conocimientos sobre la plataforma Databricks Mosaic AI y el desarrollo de agentes * Experiencia con arquitecturas de IA basadas en agentes: agentes autónomos, sistemas multiagente y orquestación * Databricks MLflow, AutoML y Vector Search * Integración y ajuste de modelos base (OpenAI, Anthropic) * Dominio del Mosaic AI Agent Framework para crear, probar e implementar agentes de IA * Arquitecturas RAG, técnicas de incrustación y LangChain/LangGraph * Diseño de flujos de trabajo de agentes con intervención humana y toma de decisiones autónoma * Sólidos conocimientos de Python (PyTorch/TensorFlow, marcos de aprendizaje automático distribuido) * Conocimiento de las mejores prácticas de MLOps y de las estrategias de implementación de modelos Ingles avanzado ## Description que ofrezca rutas recomendadas, SDK, interfaces de línea de comandos (CLI), plantillas y patrones de evaluación. ## Related Videos - [Fully Orchestrating Databricks from Airflow](https://www.wearedevelopers.com/videos/336-fully-orchestrating-databricks-from-airflow) - [Photonic Computing: Programming a New Class of AI Accelerators (incl. Live Coding)](https://www.wearedevelopers.com/videos/100196-photonic-computing-programming-a-new-class-of-ai-accelerators-incl-live-coding) - [Machine learning in the browser with TensorFlowjs](https://www.wearedevelopers.com/videos/155-machine-learning-in-the-browser-with-tensorflowjs) - [Data Analytics with Microsoft Fabric: End-to-End Use Case with Data Agents](https://www.wearedevelopers.com/videos/1547-data-analytics-with-microsoft-fabric-end-to-end-use-case-with-data-agents) - [Beyond Prompting: Building Scalable AI with Multi-Agent Systems and MCP](https://www.wearedevelopers.com/videos/1454-beyond-prompting-building-scalable-ai-with-multi-agent-systems-and-mcp) - [Serverless deployment of (large) NLP models ](https://www.wearedevelopers.com/videos/158-serverless-deployment-of-large-nlp-models) ## Related Articles - [Everything a Developer Needs to Know About MCP with Neo4j](https://www.wearedevelopers.com/magazine/604-everything-a-developer-needs-to-know-about-mcp-with-neo4j) - [Coffee with Developers - Maria Apazoglou - Making AI understandable for all in production](https://www.wearedevelopers.com/magazine/475-coffee-with-developers-maria-apazoglou-making-ai-understandable-for-all-in-production) - [Graph and AI Trends 2026: Why Is AI Running but Not Yet Delivering?](https://www.wearedevelopers.com/magazine/680-graph-and-ai-trends-2026-why-is-ai-running-but-not-yet-delivering) - [MLOps – What’s the deal behind it?](https://www.wearedevelopers.com/magazine/125-mlops-what-s-the-deal-behind-it) - [Dev Digest 164: AI Agents, AI Blindspots and MCP security problems](https://www.wearedevelopers.com/magazine/578-dev-digest-164-ai-agents-ai-blindspots-and-mcp-security-problems) - [MLops – Deploying, Maintaining And Evolving Machine Learning Models in Production](https://www.wearedevelopers.com/magazine/115-mlops-deploying-maintaining-and-evolving-machine-learning-models-in-production)