Sr Director, Enterprise Data & AI Architecture, Orthopedics

Job description

At Johnson & Johnson, we believe health is everything. Our strength in healthcare innovation empowers us to build a world where complex diseases are prevented, treated, and cured, where treatments are smarter and less invasive, and solutions are personal. Through our expertise in Innovative Medicine and MedTech, we are uniquely positioned to innovate across the full spectrum of healthcare solutions today to deliver the breakthroughs of tomorrow, and profoundly impact health for humanity. Learn more at jnj.com As guided by Our Credo, Johnson & Johnson is responsible to our employees who work with us throughout the world. We provide an inclusive work environment where each person is considered as an individual. At Johnson & Johnson, we respect the diversity and dignity of our employees and recognize their merit. Job Function: Enterprise Management Job Sub Function: Technology Management Job Category: People Leader All Job Posting Locations: Raritan, New Jersey, United States of America Job Description: Role OverviewThis is a critical executive leadership role responsible for defining, governing, and evolving the enterprise-wide Data, Analytics, AI, and Digital Architecture strategy for a newly forming standalone company. Reporting directly to the Chief Data & Analytics Officer (CDAO), the Chief Data & AI Architect serves as the senior-most technology and architecture authority for all data and AI platforms, products, and capabilities across the enterprise. The role requires a highly experienced technology leader with deep expertise in modern data architecture, cloud platforms, AI/ML engineering, Generative AI, Agentic AI, enterprise integration, and large-scale data transformation programs. This individual will establish the target-state architecture, technology standards, operating model, and investment roadmap to build a scalable, secure, and intelligent enterprise platform that accelerates business growth and innovation. The Chief Data & AI Architect will partner closely with executive leadership, business functions, enterprise technology teams, and global capability centers (GCCs) to ensure all data and AI investments align with enterprise strategy while enabling new AI-driven ways of working. This is a unique opportunity to architect and build a modern Data & AI ecosystem from the ground up, leveraging cloud-native technologies, intelligent automation, agentic workflows, advanced analytics, and emerging AI capabilities that will define the future operating model of the organization. Key ResponsibilitiesEnterprise Data & AI Architecture Leadership Define and own the enterprise-wide Data, AI, Analytics, and Information Architecture strategy, standards, principles, reference architectures, and multi-year roadmap. Serve as the organization's principal architect and trusted advisor to the CDAO, executive leadership, and technology teams on all data and AI-related investments and decisions. Establish the target-state architecture for enterprise data platforms, AI ecosystems, digital products, knowledge systems, and intelligent automation capabilities. Data Platform & Modern Data Architecture Design and oversee modern cloud-native data architectures including Data Warehouses, Data Lakes, Lakehouse platforms, Data Mesh, Data Fabric, Metadata Management, Master Data Management (MDM), and Data Products. Lead architectural decisions for enterprise-scale data ingestion, integration, streaming, event-driven architectures, API ecosystems, and real-time analytics platforms. Define scalable patterns for data interoperability across ERP, CRM, Manufacturing, Medical, Commercial, and Enterprise systems. AI, Generative AI & Agentic Architecture Architect enterprise AI platforms supporting Machine Learning, Predictive Analytics, Generative AI, Retrieval-Augmented Generation (RAG), Knowledge Graphs, Vector Databases, and Multi-Agent Systems. Define the enterprise strategy for Agentic AI capabilities, autonomous workflows, AI assistants, digital workers, intelligent orchestration, and human-in-the-loop operating models. Establish architecture patterns for AI governance, model lifecycle management, prompt engineering, agent orchestration, model evaluation, observability, and Responsible AI. Lead adoption of emerging AI technologies and drive the transformation of business processes through AI-powered ways of working. Platform Engineering & Technology Modernization Define technology standards and engineering practices across cloud infrastructure, platform engineering, DevSecOps, MLOps, LLMOps, and DataOps. Lead platform modernization initiatives that improve scalability, resiliency, performance, automation, and developer productivity. Drive enterprise adoption of reusable architecture patterns, accelerators, frameworks, and reference implementations. Data Governance, Security & Compliance Establish enterprise standards for data governance, privacy, security, lineage, metadata, quality, retention, access management, and regulatory compliance. Partner with cybersecurity and risk teams to ensure secure and compliant use of enterprise data and AI capabilities. Implement governance frameworks supporting responsible, ethical, and auditable AI adoption. Business & Technology Alignment Partner with business executives to translate strategic priorities into technology architecture and platform investments. Collaborate with enterprise technology teams to ensure alignment between business capabilities, applications, data platforms, and AI solutions. Define business capability maps, technology roadmaps, and value realization frameworks supporting long-term enterprise objectives. GCC & Global Delivery Leadership Act as the primary architecture authority for GCC execution teams and development organizations. Establish architecture review boards, governance processes, and delivery standards across global delivery teams. Drive architectural consistency, quality, and scalability across all data, analytics, and AI initiatives executed through global teams. Organizational Leadership Build and lead a high-performing team of enterprise architects, solution architects, AI architects, data engineers, and platform leaders. Mentor senior technical leaders and create a culture of innovation, engineering excellence, and continuous learning. Serve as an industry thought leader in AI, data strategy, enterprise architecture, and intelligent automation. QualificationsEducationBachelor's degree in Computer Science, Information Systems, Engineering, Data Science, Artificial Intelligence, or related discipline required. Master's degree, MBA, or PhD preferred. Experience & SkillsRequired15+ years of progressive experience in Enterprise Architecture, Data Architecture, AI Platforms, or Technology Leadership roles. Proven experience serving as a Chief Architect, Enterprise Architect, Distinguished Architect, or equivalent senior technical leadership position. Deep expertise in modern Data Warehousing, Lakehouse Architecture, Data Fabric, Data Mesh, MDM, Metadata Management, and Enterprise Analytics platforms. Strong hands-on architectural expertise across cloud platforms including Azure, AWS, and/or Google Cloud. Extensive experience designing enterprise AI, Machine Learning, Generative AI, Agentic AI, RAG, Vector Database, Knowledge Graph, and Intelligent Automation solutions. Demonstrated experience establishing enterprise AI governance, Responsible AI frameworks, MLOps, LLMOps, Model Lifecycle Management, and AI security practices. Strong understanding of modern integration technologies including APIs, microservices, event-driven architecture, streaming platforms, and enterprise integration patterns. Proven success leading large-scale enterprise data transformations and developing technology roadmaps spanning multiple business functions. Experience managing architecture governance, technology standards, reference architectures, and enterprise design authorit