Vice President of Data & AI Platforms

Johnson & Johnson Innovative Medicine•Raritan, NJ

About The Position

The Vice President of Data & AI Platforms is a senior technology executive responsible for transforming Johnson & Johnson into a truly data driven, AI enabled enterprise. This leader defines and drives J&J’s strategy for enterprise data platforms, advanced analytics infrastructure, AI/ML (including Generative AI) product development, and AI governance & ethics. The VP’s mandate is to unlock the value of J&J’s vast data assets through scalable platforms and innovative AI solutions that accelerate R&D, enhance supply chain resilience, personalize customer engagement, and improve operational efficiency. A core part of this role is ensuring that trusted data and AI tools are broadly accessible across the company by partnering with Technology Services (TS) peers and business units (sectors/functions), J&J Data Management Council to decentralize execution while maintaining strategic alignment. Importantly, this VP now also directly oversees J&J’s internal Generative AI platforms and tools including the company’s “Intelligent Chat” enterprise chatbot, LLM API Marketplace, Content Sphere knowledge retrieval platform, Agentic AI workflow framework, Draft Assist document generator and Orchestration Platform and the GenAI Governance Portal. By advancing and scaling these capabilities under robust governance, the VP will shape how data and GenAI technologies power innovation and competitive advantage at J&J, all while upholding Our Credo values and rigorous ethical standards. This position reports to the Global CTO and is a key member of the Technology Services Leadership Team, leading a global organization (~100 staff) across data engineering, data integration, AI platforms, AI enablement, and data/AI governance. The role is based in Raritan, NJ, with a global remit and will require international travel to support worldwide teams and initiatives

Requirements

15+ years of progressive IT experience, with significant time in executive data and analytics roles (e.g., Head of Data & Analytics, Chief Data Officer, Head of AI/ML).
Proven leadership in large-scale, enterprise data platform implementations and advanced analytics/AI deployments delivering measurable business value.
Deep expertise managing end-to-end data pipelines and platforms, including cloud data lakes, integration, warehousing, and analytics provisioning.
Extensive experience leading AI/ML projects in production and operationalizing ML models at scale, with exposure to Generative AI and modern AI technologies (LLMs, NLP, automation).
Demonstrated success in building or scaling enterprise AI capabilities, including infrastructure, governance, and cross-functional adoption processes.
Strong technical acumen in data engineering and AI, including cloud platforms (AWS, Azure, GCP), big data technologies (Spark, Hadoop), and AI/ML frameworks (TensorFlow, PyTorch).
Expertise in data governance, security, and compliance, with the ability to uphold trust and ethical standards in data and AI.
Strategic vision and business acumen, linking data/AI initiatives to business outcomes and communicating value to senior stakeholders.
Exceptional leadership and people management, with experience leading Senior Leaders of large, global teams and driving organizational change.
Execution-focused, with a track record of delivering major data/AI programs on time and within budget, and strong financial management skills.
Industry experience in healthcare, pharma, or medical devices preferred; experience in other large, regulated, innovation-driven sectors valued.
Hands-on or oversight experience with Generative AI implementations and emerging AI technologies; thought leadership (publications, patents, conferences) a plus.
Global/multicultural experience leading international teams and navigating diverse regulatory and cultural environments.
20% travel required
10 Years people management experience

Nice To Haves

An advanced degree (Master’s or Ph.D. in a relevant technical field, or an MBA with a technology focus) is highly preferred given the strategic and technical breadth of this role

Responsibilities

Enterprise Data Platforms & Quality: Own end-to-end data engineering and platform operations for J&J’s enterprise data ecosystem. Manage the design, development, and 24x7 operation of scalable, secure, and AI-ready data pipelines that ingest and integrate data from all key domains (R&D, Commercial, Supply Chain, Finance, etc.) into a modern, cloud-based data framework. Ensure high-quality, well-governed data by driving timely ingestion, transformation, and reconciliation of both structured and unstructured data across the company. This involves championing robust data management practices (data cleansing, master data management, metadata cataloging) so that J&J’s data is “single-source-of-truth” and ready for analytics/AI usage. Success in this area means J&J’s analysts and data scientists spend far less time on data prep and trust the accuracy of data (e.g. targeting >50% reduction in data preparation effort through better data quality and integration). The VP also aligns data platform architecture with Enterprise Architecture standards and Security/Privacy requirements – embedding compliance with HIPAA, GDPR, and internal policies into all data processes. In summary, this leader ensures J&J’s data foundations are strong, reliable, and primed for AI, enabling faster insights and better business decisions globally
Data Platform & Architecture Ownership: Oversee the design and operation of J&J’s core data stores and infrastructures, including cloud-based data lakes, data warehouses, and emerging GenAI/“Agentic AI” platforms. As the top data architect, champion modern, scalable data architecture paradigms – for example, implementing a “data lakehouse” approach that combines the flexibility of data lakes with the structure of warehouses, leveraging streaming data pipelines for real-time needs, and exploring data fabric concepts for unified data access. This VP owns the reference architecture for data and AI systems: setting technology standards and design patterns that guide how data platforms and AI solutions are built across J&J. That includes selecting and integrating the right cloud technologies, database systems, big data tooling, and ensuring these components work together seamlessly. A key focus is integrating GenAI and analytics into the architecture – e.g. making sure that the infrastructure supports large-scale training/inference, providing vector databases and knowledge graphs to power LLM applications. The VP continuously evaluates and upgrades the architecture for performance, cost-efficiency, and scalability. For instance, in 2026 the strategy may involve further consolidation of on-premise data warehouses into cloud platforms, deploying serverless or auto-scaling technologies to handle growth efficiently, and ensuring network/connectivity aspects (in partnership with Infrastructure) are robust for global data flows. Ultimately, the VP’s accountability is a future-ready data platform architecture that can accommodate the explosion of data and AI workloads, while remaining secure and compliant
GenAI & AI Platforms and Product Development: Lead the development and scaling of J&J’s AI/ML platforms and Generative AI solutions, serving both technical teams and end-users. This includes building and managing enterprise-wide platforms for machine learning operations (MLOps) – ensuring robust model lifecycle management from experimentation to deployment to monitoring. The VP oversees the creation of orchestration layers and integration frameworks that allow AI models and algorithms to plug into business processes and applications. This leader owns J&J’s internal Generative AI platform products (originally incubated by TS Architecture/GenAI team) and will drive their evolution and broad adoption. These include the Intelligent Chat chatbot, the LLM API Marketplace (a one-stop API layer for accessing various large language models across Azure OpenAI, AWS Bedrock, etc.), the Content Sphere retrieval-augmented generation platform (enabling AI Q&A against enterprise documents and knowledge), the Agentic AI Framework (a low-code toolkit to develop AI agents and workflows), and Draft Assist (an AI-powered document drafting and content generation tool). The VP also stewards the GenAI Governance Portal (GovernAI), which manages AI use-case approvals and compliance workflows. By consolidating these GenAI products under one umbrella, the VP ensures they are secure, scalable, and delivering value. Key tasks include enhancing these platforms with new capabilities (for example, integrating the latest GPT-5/Claude models as they become available, enabling multi-cloud deployments for resilience, and improving features like “digital front door” unified chat access), while also optimizing performance and cost (e.g. managing the Provisioned Throughput Units for LLM hosting to meet demand efficiently). The VP will work closely with the VP of End user services to align the broader AI strategy on CoPilot Premium including determining the future of J&J Intelligent Chat. The VP is accountable for the performance, quality, and compliance of all AI solutions and platforms in J&J, from advanced analytics models to generative AI services. This means instituting rigorous testing/validation for AI products, monitoring model outcomes and system usage, and quickly addressing any issues in output quality or reliability. By providing world-class AI and GenAI platforms, this leader enables data scientists, engineers, and even citizen developers across J&J to rapidly develop AI solutions that are production-grade, thus significantly accelerating J&J’s overall AI innovation.
Data Services & Integration: Deliver enterprise data services and integration capabilities that make J&J’s data both accessible and actionable throughout the business. This responsibility covers a broad set of data-centric services, including enterprise data integration platforms (to connect and transform data between systems), data APIs and microservices, and business intelligence (BI) and analytics tools. The VP’s team provides reliable data integration pipelines and enterprise integration services that allow various applications (ERP, CRM, lab systems, etc.) to share data seamlessly, reducing silos. Additionally, this leader ensures J&J has robust self-service analytics and BI platforms – such as the governance and support of tools like Tableau, Power BI or other visualization environments – so that business users and analysts can easily access and analyze data without heavy IT involvement. The VP drives initiatives to improve the usability and reach of data services: for example, establishing a data marketplace or catalog that lets employees discover available data sets, or creating standardized data products (like common data models for customer or product data) that multiple teams can leverage. A key goal is to democratize data access and insights across the enterprise: success is measured by increased adoption of self-service data tools, reduced cycle time for analytics (e.g., automatically generating certain reports with AI assistance), and high satisfaction from business stakeholders who feel their data needs are met quickly. The VP also defines and tracks KPIs for data service performance and usage – such as data pipeline reliability (uptime, latency), number of active users of analytics tools, and turnaround time for integration requests – and implements continuous improvements. By delivering robust data services, this leader ensures that data is readily available and consumable where and when it’s needed, which is the foundation for all advanced analytics and AI initiatives.
AI Governance, Risk & Ethics: In partnership with the GenAI Governance Board, act as J&J’s ve steward for responsible AI, ensuring that all Gen AI activities adhere to the highest standards of ethics, quality, and compliance. The VP chairs the GenAI Governance Council and is a key member of broader data/AI governance bodies (such as J&J’s Data Management Council and AI Council). In this role, implement and enforce enterprise-wide AI governance policies – covering areas like bias mitigation, model validation, transparency, and regulatory compliance. For example, the VP will oversee processes to test AI models for bias or errors before deployment, to validate models especially in high-risk use cases (like GxP-regulated manufacturing or clinical decision support), and to ensure privacy and data protection for any AI that uses sensitive data. This leader’s team maintains a central inventory of Gen AI models and algorithms in use across J&J, along with their intended purpose, training data, and risk assessments; laying the groundwork for model lifecycle governance. They also manage the GenAI use-case review process via the GovernAI portal, streamlining approvals while capturing necessary oversight (e.g., the introduction of a “Fast Track” for low-risk AI experiments which now approves ~25% of use cases instantly). The VP ensures the GenAI Governance process stays ahead of emerging complexities for instance, as new AI paradigms like autonomous agents become more common, governance criteria and technical guardrails are updated accordingly. Success in governance means that J&J avoids major AI-related incidents or ethical lapses: no unauthorized use of protected data, no uncontrolled “rogue” AI deployments, and no reputational damage from AI outcomes. Additionally, this VP champions explainable and transparent AI, working with technical teams to implement features like model explainability reports or bias dashboards so that business leaders and regulators can understand AI-driven decisions. By fostering a culture of “AI with integrity,” the VP helps maintain stakeholder trust and aligns J&J’s AI push with its Credo and compliance obligations.
Enterprise AI Enablement & Adoption (Strategy & Oversight): Partner with JJT Strategy and Operations team in driving enterprise-wide AI enablement and literacy to ensure J&J’s businesses successfully adopt AI solutions at scale. This team co-owns the AI/GenAI enablement strategy in partnership with the TS Strategy & Operations team, but critically, allows sectors and functions to lead execution of AI use cases in their domains (a federated model). This leader’s role is to provide the common platforms, frameworks, and training that empower those distributed teams to implement AI effectively. Together they provide toolkits and best-practice playbooks for AI project execution, covering how to identify good AI opportunities, how to build with J&J’s GenAI tools, how to measure benefits, etc.. The VP also coordinates a federated “AI Community of Practice” connecting data scientists, AI product owners, and business analysts across sectors. Through this community, they share successful use cases, avoid duplication of efforts (e.g., preventing multiple teams from building similar NLP solutions by encouraging reuse of one platform or model), and surface needs that the central team can support. The VP regularly tracks and reports on AI adoption metrics: for instance, what percentage of business units have deployed at least one AI solution, or what proportion of employees are actively using the “AI for All” productivity tools (the target is to reach >70% of employees using AI tools monthly by end of 2026). They intervene to address adoption barriers – whether technical (scaling issues), skill gaps, or cultural resistance partnering with HR and change management teams to do so. In summary, the VP acts as J&J’s AI evangelist and enabler, making sure the great tools and data are actually put to use in delivering business outcomes, and that the workforce is both excited about and capable of leveraging AI day-to-day
Leadership & Organizational Management: Provide strong vision and management for a global Data & AI Platforms organization (~100 professionals) that spans multiple continents and disciplines. Directly oversee senior leaders and directors in areas including Data Engineering & Platforms, Data Services & Integration, AI Platforms & Engineering, AI Enablement & Performance, and Data & AI Governance (per the 2026 TS org design). This VP must establish a clear organizational structure with well-defined roles and foster a culture of innovation, accountability, and inclusion. The VP champions talent development: attract and retain top-tier talent in engineering and AI/Gen AI skills by promoting J&J’s exciting mission (e.g., applying AI to improve patient outcomes). Invest in upskilling internal talent – for instance, training traditional data engineers in cloud-based AI tools, or converting business analysts into citizen data scientists through mentorship and coursework. Inclusion is emphasized in hiring and team culture, recognizing that diverse teams produce more robust, unbiased AI solutions. The VP ensures the team stays highly engaged and motivated by providing growth opportunities and recognition for accomplishments. As part of TS leadership team, this role also involves cross-functional collaboration and contributing to overall IT strategy: the VP works closely with peers in Infrastructure, Security, Enterprise Architecture, and Business Technology groups to align initiatives and share resources. This leader must be adept at managing a matrix environment, since many data & AI team members will work day-to-day with business units or other IT teams. Performance management is key: set clear OKRs for each sub-team (e.g., data platform uptime, number of AI use cases delivered, user adoption stats, etc.) and hold leaders accountable. Ultimately, this VP’s leadership will be reflected in a high-performing, agile, and business-focused Data/AI function that is viewed as one of the best in the industry, and in J&J’s reputation as a leader in leveraging data and AI (e.g., speaking at conferences, case studies with tech partners).
Performance Measurement & Value Realization: Ensure that data and AI initiatives deliver measurable business value and continuously improve over time. The VP establishes a strong value-tracking framework for all significant Data/AI projects – partnering with Finance and business stakeholders to quantify outcomes in terms of the 3E’s (Efficiency, Effectiveness, and Experience) or direct ROI. This includes setting target KPIs at project start (e.g., “AI-driven inventory optimization will reduce excess stock by 20%, saving $X million”) and then tracking actuals post-implementation. The VP’s team produces regular dashboards/reporting on the impact of AI across J&J, such as aggregate efficiency gains. Notably, with the new GenAI platforms, track enterprise productivity improvements: for example, it’s estimated that J&J’s general GenAI productivity tools (Intelligent Chat, Copilot, etc.) are yielding >$80M per year in time savings/value by late 2025 – the VP will validate and expand on these figures as usage grows. They also measure adoption and usage statistics (inputs to value) and use these metrics to make decisions – if a certain AI tool is under-utilized but high value, invest in marketing it internally; if a certain project isn’t yielding as expected, investigate and course-correct or terminate. The VP fosters a culture of data-driven decision-making within TS itself, using metrics to drive prioritization. Additionally, embed continuous improvement loops: results and user feedback from deployed solutions feed into the backlog for enhancements or next phases. The goal is transparency and accountability: the C-suite and business leaders should have clear line of sight into what Data & AI initiatives are doing for the company’s bottom line, and the VP stands ready to explain and optimize that performance. Over a 1-2 year horizon, this leader aims to show significant contributions of data/AI to J&J’s strategic goals – e.g., cycle time reductions in drug development due to AI analysis, improved customer satisfaction via AI personalization, or cost avoidance through better forecasting. By rigorously measuring outcomes, the VP ensures J&J’s investments in data and AI are justified and are maximized for impact.
External Engagement & Thought Leadership: Represent J&J as a thought leader in the global data and AI community. The VP will engage externally to keep a pulse on industry innovation and to promote J&J’s progress. This involves speaking at industry conferences, participating in technology leadership forums, and forging strategic partnerships. By maintaining visibility into emerging technologies and best practices, this leader ensures J&J’s data & AI strategy stays ahead of the curve. Additionally, their involvement in external circles can help in recruiting top talent and enhancing J&J’s brand as a tech innovator. In summary, the VP balances internal execution with an outward-looking perspective, ensuring J&J’s Data & AI capabilities are both leading and evolving with the broader tech ecosystem

Benefits

Subject to the terms of their respective plans, employees are eligible to participate in the Company’s consolidated retirement plan (pension) and savings plan (401(k)).
This position is eligible to participate in the Company’s long-term incentive program.
Subject to the terms of their respective policies and date of hire, employees are eligible for the following time off benefits:
Vacation –120 hours per calendar year
Sick time - 40 hours per calendar year; for employees who reside in the State of Colorado –48 hours per calendar year; for employees who reside in the State of Washington –56 hours per calendar year
Holiday pay, including Floating Holidays –13 days per calendar year
Work, Personal and Family Time - up to 40 hours per calendar year
Parental Leave – 480 hours within one year of the birth/adoption/foster care of a child
Bereavement Leave – 240 hours for an immediate family member: 40 hours for an extended family member per calendar year
Caregiver Leave – 80 hours in a 52-week rolling period10 days
Volunteer Leave – 32 hours per calendar year
Military Spouse Time-Off – 80 hours per calendar year