Technical Product Owner – Lead AI Engineer

Jobtailor; Milano; In loco; EUR 90.000 - 130.000; Tempo pieno

Descrizione del lavoro

Jobtailor is seeking a seasoned AI Engineering leader to drive the development and delivery of enterprise AI solutions. You will own AI product strategy, collaborate with stakeholders, and guide squads across multiple domains to deliver measurable business value.

Responsibilities include designing scalable AI systems, ensuring governance and security, and aligning with regulatory standards while leading Agile teams and data platform initiatives.

Competenze

• 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.

Mansioni

• 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.

Conoscenze

Data Science

Machine Learning

AI Engineering

Leadership

Agile

Formazione

Bachelor's or Master's in Computer Science / Data Science / Engineering / AI

Strumenti

Azure

AWS

GCP

Vector Databases

RAG

AI agent frameworks

Descrizione del lavoro

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.