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, and delivery organizations.
Ensure complian
📌 Lead Data AI Engineer (Milano)
🏢 Altro
📍 Milano