Dir Tech Prod Mgmt

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Role Overview

The Director AI Fabric and Data Platforms is accountable for leading the enterprise AI Services and Data Foundation capability ensuring scalable secure and high-impact delivery of end-to-end AI services across the organization. The role owns the full lifecycle of AI services from vision and roadmap definition through design deployment customer enablement and operationalization while ensuring sustained business value and operational excellence.

In addition the role leads the evolution of a unified AI Agent Factory platform one shared platform one access layer one compliance framework and one playbook designed to produce reusable AI agents that own and automate end-to-end business workflows across functions.

The role is also responsible for the Data Platforms strategy and execution enabling trusted governed and reusable data assets that power AI analytics and digital products at scale.

Key Responsibilities

Strategy Platform Vision & Roadmap

• Define and execute the AI Fabric and Data Foundation strategy and roadmap positioning the AI Agent Factory as a core enterprise platform.
• Own the end-to-end lifecycle of AI services and agents ensuring seamless transition from innovation to production and scaled adoption.
• Design a unified operating model enabling multiple AI Factories (e.g. Insights Engagement Content) to deliver domain-specific value.

Delivery & Execution

• Lead end-to-end delivery of AI services from ideation and experimentation to deployment adoption by end customers and ongoing operations.
• Implement repeatable delivery engines across buildtestreleasedeploy for AI and data services ensuring predictable throughput and quality.
• Ensure service continuity through strong operational readiness incident management and support processes for AI-enabled products.

Engineering Excellence (Agent-based DevOps Observability)

• Drive adoption of agent-based architectures where AI components own decisions and automate workflows end-to-end.
• Ensure reuse through a centralized catalog of AI agents data assets and services.
• Own and continuously improve engineering practices across AI and Data Foundation teams including CI/CD source control code quality and SDLC automation.

Business & Process Acumen

• Strong understanding of enterprise business processes operating models and regulatory environments and how AI and data platforms enable end-to-end outcomes.
• Ability for AI Fabric scope to engage senior stakeholders and guide teams toward scalable standardized AI and data solutions that reduce complexity and cost.

Stakeholder & Vendor Partnership

• Partner for AI Fabric scope with business product and digital teams to translate needs into scalable AI and data solutions delivering tangible business outcomes.
• Collaborate with external vendors and global technology teams to align roadmaps close capability gaps and accelerate delivery.

People Management & Leadership

• Lead coach and develop multidisciplinary teams across AI engineering data engineering platform engineering and analytics.
• Build a high-performing culture grounded in accountability ethics and continuous learning while managing performance and succession planning.

Governance Risk Security & Compliance

• Ensure the Agent Factory operates under a unified compliance framework with consistent governance across all AI services and workflows.

Metrics OKRs & Continuous Improvement

• Track for AI Fabric scope the adoption of AI agents workflow automation rates reuse of platform components and business impact.

Budget Management & Value Realization

• Own and manage the AI Fabric and Agent Factory budget ensuring optimal allocation across platform product development operations and innovation.
• Drive cost efficiency and transparency balancing investments between foundational capabilities and business-driven use cases.
• Partner with finance and stakeholders to ensure financial governance forecasting accuracy and continuous value realization.

Qualifications

Required

• Bachelors (or higher) degree in Computer Science Engineering Data Science or a related field.
• Proven experience leading AI data or platform teams with end-to-end service ownership.
• Strong knowledge of modern SDLC DevOps practices and agile delivery models.
• Excellent communication skills with the ability to bridge technical and business stakeholders.

Preferred

• Experience with cloud-native AI and data platforms.
• Exposure to generative AI and advanced analytics use cases in enterprise environments.
• Strong understanding of data governance security and compliance concepts.

Required Skills:

Preferred Skills:

The anticipated base pay range for this position is:

Benefits:

In addition to base pay we offer the following benefits*: 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. Moreover we offer 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. We also offer service anniversary and recognition awards and subject to the terms of their respective plans employees - and in some locations eligible dependents - can participate in several insurance plans. For more information visit Employee benefits Supporting well-being & career growth Johnson & Johnson Careers.

*This is for informative purposes only. Amounts and actual benefits may vary by location and are subject to change.