Technical Product Owner – Lead AI Engineer

Johnson & Johnson

Lead AI Engineer at Johnson & Johnson responsible for AI solutions design and deployment. Collaborating with multidisciplinary teams to create measurable business value.

Posted 7/11/2026full-timeMilan • 🇮🇹 ItalySenior💰 €48,600 - €77,395 per yearWebsite

Tech Stack

Tools & technologies

AWSAzureCloudETLGoogle Cloud Platform

About the role

Key responsibilities & impact

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.

Requirements

What you’ll need

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.

Benefits

Comp & perks

an annual bonus with set target (% of pay) depending on pay grade / location, where the actual amount is based on the employees’ and companies’ performance of the previous calendar year, or sales commissions.
vacation days
parental leave for a minimum of 12 weeks
bereavement leave
caregiver leave
volunteer leave
well-being reimbursement
programs for financial, physical and mental health
service anniversary and recognition awards
employees - and in some locations eligible dependents - can participate in several insurance plans.

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills & Tools

Machine LearningGenerative AIPredictive AnalyticsMLOpsData PipelinesETL/ELTModel GovernancePerformance MonitoringAI Agent FrameworksVector Databases

Soft Skills

CollaborationLeadershipCommunicationProblem-SolvingStakeholder Management

Certifications

Bachelor's or Master's Degree in Computer Science, Data Science, Engineering, or Artificial Intelligence