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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Chief Data & AI Architect - **Company:** Johnson & Johnson - **Location:** Raritan, NJ, United States - **Experience:** Expert - **Salary:** $178,000.0 - $307,050.0 - **Contract:** Permanent contract - **Skills:** Application Programming Interfaces (APIs), Artificial Intelligence, Amazon Web Services, Data Analysis, Architectural Patterns, Microsoft Azure, Big Data, Cloud Computing, Cloud Engineering, Cyber Security, Information Systems, Databases, Data Architecture, Data Governance, Data Infrastructure, Data Warehousing, Digital Architecture, Graph Database, Identity and Access Management, Interoperability, Knowledge-Based Systems, Machine Learning, Meta-Data Management, Power BI, DataOps, Data Streaming, Enterprise Data Management, Google Cloud, Enterprise Software Applications, Cloud Platform System, Data Ingestion, Azure Data Factory, Snowflake, Multi-Agent Systems, Prompt Engineering, IT Architecture, Model Validation, Generative AI, Data Strategy, Event Driven Architecture, Microsoft Fabric, Data Lakes, AI Platforms, Information Technology, Data Analytics, Enterprise Integration, Data Management, Machine Learning Operations, Virtual Agents, Meditech, Azure Synapse Analytics, Devsecops, GXP, Databricks, Microservices - **Published:** July 30, 2026 - **Apply:** https://www.dice.com/job-detail/6840e53d-da61-44b5-890d-9b1ca459aca7 ## About the Role * Bachelor's degree in Computer Science, Information Systems, Engineering, Data Science, Artificial Intelligence, or related discipline required. * Master's degree, MBA, or PhD preferred., * 15+ 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 authorities. * Ability to influence executive stakeholders and drive strategic technology decisions at the Board, Executive Committee, and C-Suite levels. * Experience leading global teams and operating within GCC-based delivery models. Preferred * Experience building the Data & AI architecture for a newly formed, divested, or standalone organization. * Deep expertise with Azure Data Platform, Databricks, Snowflake, Microsoft Fabric, Synapse, Power BI, and enterprise AI platforms. * Experience implementing enterprise-scale Copilot, GenAI, Agentic AI, and intelligent automation programs. * Experience in MedTech, Healthcare, Life Sciences, or other highly regulated industries. * Strong understanding of data privacy, cybersecurity, GxP, HIPAA, GDPR, and global regulatory requirements. * Industry-recognized certifications in Enterprise Architecture, Cloud Architecture, Data Architecture, AI/ML, or Cybersecurity. * Published thought leadership, conference speaking experience, or recognized contributions within the data and AI community. ## Description This 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., Enterprise 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 fC 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. ## Related Videos - [Blueprints for Success: Steering a Global Data & AI Architecture](https://www.wearedevelopers.com/videos/1577-blueprints-for-success-steering-a-global-data-ai-architecture) - [Beyond GPT: Building Unified GenAI Platforms for the Enterprise of Tomorrow](https://www.wearedevelopers.com/videos/1525-beyond-gpt-building-unified-genai-platforms-for-the-enterprise-of-tomorrow) - [Reference Architecture of AI in the Cloud](https://www.wearedevelopers.com/videos/1613-reference-architecture-of-ai-in-the-cloud) ## Related Articles - [Graph and AI Trends 2026: Why Is AI Running but Not Yet Delivering?](https://www.wearedevelopers.com/magazine/680-graph-and-ai-trends-2026-why-is-ai-running-but-not-yet-delivering) - [Coffee with Developers - Maria Apazoglou - Making AI understandable for all in production](https://www.wearedevelopers.com/magazine/475-coffee-with-developers-maria-apazoglou-making-ai-understandable-for-all-in-production) - [How to Become an AI Engineer](https://www.wearedevelopers.com/magazine/331-how-to-become-an-ai-engineer) - [Navigating the AI Shift](https://www.wearedevelopers.com/magazine/629-navigating-the-ai-shift) - [Best US AI Conferences for CTOs in 2026: Build vs. Buy, Vendor Evaluation, and Peer Intelligence](https://www.wearedevelopers.com/magazine/736-best-us-ai-conferences-for-ctos-in-2026-build-vs-buy-vendor-evaluation-and-peer-intelligence) - [What Industries Outside of AI Are Hiring The Most AI Experts?](https://www.wearedevelopers.com/magazine/98-what-industries-outside-of-ai-are-hiring-the-most-ai-experts)