Technical Product Owner – Lead AI Engineer
Pubblicato il 23-08-2026 - Jobtailor in Milano
Responsibilities
- Partner with business stakeholders to identify, prioritize, and deliver AI use cases aligned to strategic objectives.
- Act as Technical Product Owner (TPO) for AI products and platforms, managing backlog prioritization and roadmap execution.
- Translate business requirements into actionable technical epics, features, and user stories.
- Drive adoption of AI solutions by ensuring measurable business outcomes and user satisfaction.
- Design, develop, and deploy Machine Learning, Predictive Analytics, Generative AI, and Agentic AI solutions.
- Lead model lifecycle activities including experimentation, training, validation, deployment, monitoring, and continuous improvement.
- Establish engineering best practices covering MLOps, model governance, performance monitoring, and operational support.
- Ensure AI solutions are scalable, secure, maintainable, and compliant with enterprise standards.
- Collaborate closely with Data Engineers to design trusted, reusable, and governed data assets.
- Support the creation of robust data pipelines required for AI development and operationalization.
- Drive integration of structured and unstructured data sources across enterprise platforms.
- Contribute to AI and Data Platform architecture decisions to improve scalability and reuse.
- Lead Agile squads delivering AI products and capabilities across multiple business domains.
- Facilitate sprint planning, backlog refinement, retrospectives, and delivery governance activities.
- Remove delivery obstacles and ensure predictable execution against committed objectives.
- Promote DevOps and Agile best practices across the squad.
- Act as the bridge between business teams, product managers, architects, and engineering teams.
- Ensure AI solutions comply with security, privacy, responsible AI, and regulatory requirements.
- Define and monitor OKRs/KPIs for AI solution performance, business value realization, adoption, and operational effectiveness.
Qualifications
- Bachelor's or Master's degree in Computer Science, Data Science, Engineering, Artificial Intelligence, or related disciplines.
- 5–7+ years of experience in Data Science, Machine Learning, or AI Engineering roles.
- Demonstrated experience leading the delivery of AI and Analytics solutions in enterprise environments.
- Proven experience acting as Technical Product Owner, Delivery Lead, Lead Engineer, or Squad Lead.
- Strong knowledge of Machine Learning, Generative AI, LLMs, Vector Databases, RAG, and AI agent frameworks.
- Experience working with cloud-based AI ecosystems (Azure, AWS, or GCP).
- Understanding of Data Engineering concepts, including data pipelines, ETL/ELT, data lakes, and data warehousing.
- Experience with Agile methodologies and Scrum delivery frameworks.
Core 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.
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