ph3Responsibilities /h3 ul liPartner with business stakeholders to identify, prioritize, and deliver AI use cases aligned to strategic objectives. /li liAct as Technical Product Owner (TPO) for AI products and platforms, managing backlog prioritization and roadmap execution. /li liTranslate business requirements into actionable technical epics, features, and user stories. /li liDrive adoption of AI solutions by ensuring measurable business outcomes and user satisfaction. /li liDesign, develop, and deploy Machine Learning, Predictive Analytics, Generative AI, and Agentic AI solutions. /li liLead model lifecycle activities including experimentation, training, validation, deployment, monitoring, and continuous improvement. /li liEstablish engineering best practices covering MLOps, model governance, performance monitoring, and operational support. /li liEnsure AI solutions are scalable, secure, maintainable, and compliant with enterprise standards. /li liCollaborate closely with Data Engineers to design trusted, reusable, and governed data assets. /li liSupport the creation of robust data pipelines required for AI development and operationalization. /li liDrive integration of structured and unstructured data sources across enterprise platforms. /li liContribute to AI and Data Platform architecture decisions to improve scalability and reuse. /li liLead Agile squads delivering AI products and capabilities across multiple business domains. /li liFacilitate sprint planning, backlog refinement, retrospectives, and delivery governance activities. /li liRemove delivery obstacles and ensure predictable execution against committed objectives.



/li liPromote DevOps and Agile best practices across the squad. /li liAct as the bridge between business teams, product managers, architects, and engineering teams. /li liEnsure AI solutions comply with security, privacy, responsible AI, and regulatory requirements. /li liDefine and monitor OKRs/KPIs for AI solution performance, business value realization, adoption, and operational effectiveness. /li /ul h3Qualifications /h3 ul liBachelor's or Master's degree in Computer Science, Data Science, Engineering, Artificial Intelligence, or related disciplines. /li li5–7+ years of experience in Data Science, Machine Learning, or AI Engineering roles. /li liDemonstrated experience leading the delivery of AI and Analytics solutions in enterprise environments. /li liProven experience acting as Technical Product Owner, Delivery Lead, Lead Engineer, or Squad Lead. /li liStrong knowledge of Machine Learning, Generative AI, LLMs, Vector Databases, RAG, and AI agent frameworks. /li liExperience working with cloud-based AI ecosystems (Azure, AWS, or GCP). /li liUnderstanding of Data Engineering concepts, including data pipelines, ETL/ELT, data lakes, and data warehousing. /li liExperience with Agile methodologies and Scrum delivery frameworks. /li /ul pCore Competencies: Demonstrates expertise in leading AI product development and delivery, with a strong focus on Machine Learning, Generative AI, and data engineering practices. Capable of translating business needs into technical solutions while ensuring compliance with security and regulatory standards. /p /p #J-18808-Ljbffr

📌 Technical Product Owner – Lead AI Engineer (Milano)
🏢 Jobtailor
📍 Milano