Responsibilities
- Act as Technical Product Owner (TPO) for AI Data Engineering products, capabilities, and platforms.
- Partner with business stakeholders, AI teams, and architects to translate business requirements into scalable data and AI engineering solutions.
- Define and prioritize platform backlogs, technical roadmaps, and delivery plans.
- Drive adoption of reusable data products, AI services, and platform capabilities across multiple business domains.
- Design, develop, and maintain scalable data pipelines supporting AI, Analytics, Machine Learning, and Generative AI use cases.
- Lead implementation of batch, streaming, and real-time data integration capabilities.
- Build trusted and governed data assets supporting enterprise AI use cases.
- Drive engineering standards for data quality, observability, lineage, monitoring, and reliability.
- Ensure data platforms are secure, scalable, resilient, and compliant with enterprise standards.
- Enable AI solution delivery through feature stores, vector databases, model deployment pipelines, and data services.




- Support implementation of Generative AI, LLM, RAG, and Agentic AI architectures through scalable data foundations.
- Collaborate with AI Engineers and Data Scientists to operationalize AI solutions.
- Establish and maintain MLOps and DataOps practices.
- Design and operate cloud-native AI and Data Platforms.
- Define architecture patterns for data ingestion, transformation, storage, governance, and consumption.
- Optimize platform performance, scalability, reliability, and cost efficiency.
- Lead implementation of Infrastructure-as-Code, CI/CD, monitoring, and observability frameworks.
- Lead Agile squads delivering AI Data Engineering and platform capabilities.
- Facilitate sprint planning, backlog refinement, technical reviews, and delivery governance.
- Promote DevOps, DataOps, and Agile engineering best practices.
- Act as the bridge between business stakeholders, AI teams, platform teams, architects, a

📌 Lead Data AI Engineer (Milano)
🏢 Jobtailor
📍 Milano