Sr Director, Enterprise Data & AI Architecture, Orthopedics

Johnson & Johnson Johnson & Johnson · Pharma · Raritan, NJ +1

Executive leadership role defining, governing, and evolving enterprise-wide Data, Analytics, AI, and Digital Architecture strategy for a new company. Responsible for target-state architecture, technology standards, and investment roadmap for scalable, secure, and intelligent platforms. Partners with leadership to enable AI-driven ways of working and architect a modern Data & AI ecosystem from the ground up.

What you'd actually do

  1. Define and own the enterprise-wide Data, AI, Analytics, and Information Architecture strategy, standards, principles, reference architectures, and multi-year roadmap.
  2. Architect enterprise AI platforms supporting Machine Learning, Predictive Analytics, Generative AI, Retrieval-Augmented Generation (RAG), Knowledge Graphs, Vector Databases, and Multi-Agent Systems.
  3. Define the enterprise strategy for Agentic AI capabilities, autonomous workflows, AI assistants, digital workers, intelligent orchestration, and human-in-the-loop operating models.
  4. Establish enterprise standards for data governance, privacy, security, lineage, metadata, quality, retention, access management, and regulatory compliance.
  5. Partner with business executives to translate strategic priorities into technology architecture and platform investments.

Skills

Required

  • Data Architecture
  • Cloud Platforms
  • AI/ML Engineering
  • Generative AI
  • Agentic AI
  • Enterprise Integration
  • Large-scale data transformation
  • Modern cloud-native data architectures (Data Warehouses, Data Lakes, Lakehouse, Data Mesh, Data Fabric, MDM)
  • Data ingestion, integration, streaming, event-driven architectures, API ecosystems, real-time analytics
  • AI governance
  • Model lifecycle management
  • Prompt engineering
  • Agent orchestration
  • Model evaluation
  • Observability
  • Responsible AI
  • Cloud infrastructure
  • Platform engineering
  • DevSecOps
  • MLOps
  • LLMOps
  • DataOps
  • Data governance
  • Data privacy
  • Data security
  • Data lineage
  • Metadata management
  • Data quality
  • Data retention
  • Access management
  • Regulatory compliance

Nice to have

  • Knowledge Graphs
  • Vector Databases
  • Multi-Agent Systems
  • Human-in-the-loop operating models
  • Reusable architecture patterns
  • Accelerators, frameworks, and reference implementations

What the JD emphasized

  • critical executive leadership role
  • senior-most technology and architecture authority
  • highly experienced technology leader
  • deep expertise
  • architect and build a modern Data & AI ecosystem from the ground up
  • enterprise-wide Data, AI, Analytics, and Information Architecture strategy
  • principal architect and trusted advisor
  • enterprise AI platforms
  • Agentic AI capabilities
  • Responsible AI
  • enterprise standards for data governance
  • regulatory compliance

Other signals

  • 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.