Director, AI Discoverability and Evidence Architecture

Job Description

Digital Human Health is establishing a new enterprise capability to ensure our Company’s approved scientific evidence, content, and digital experiences are discoverable, accurately understood, authoritatively represented, cited, and trusted across AI-mediated ecosystems.

The Director, AI Discoverability & Evidence Architecture, within the Digital Marketing & Channels organization, will define the strategy and lead capability development and execution across AI Search Readiness, Generative Engine Optimization (GEO), LLM as a Customer, and Evidence Architecture.

Working across Medical, Commercial, Corporate Communications, and Digital Human Health, this leader will build new enterprise capabilities that strengthen our Company’s authority, visibility, and narrative accuracy in AI-generated experiences, ensuring that patients, healthcare professionals, and other stakeholders receive trusted, scientifically grounded information in an increasingly AI-mediated healthcare landscape.

Key Responsibilities

Enterprise Strategy & Capability Leadership:

• Define our Company’s long-term AI Discoverability and AI Search Readiness strategy.
• Establish the vision, roadmap, governance model, and investment strategy for GEO and AI Discoverability capabilities.
• Lead evolution of Project Oak and LLM as a Customer initiative into sustainable enterprise services.
• Develop and maintain a multi-year roadmap aligned to business priorities and AI acceleration objectives.

AI Search Readiness:

• Establish repeatable frameworks for assessing AI discoverability opportunities, evidence gaps, narrative vulnerabilities, and competitive risks across pipeline and inline brands.
• Lead AI Search Readiness assessments, strategic recommendations, activation roadmaps, and remediation planning for priority brands and therapeutic areas.
• Integrate AI Search Readiness into relevant launch, evidence, content, brand, and digital experience planning processes.
• Develop scalable service models, playbooks, and engagement approaches that enable adoption across brands, functions, and markets.

Evidence Architecture & Ontology Strategy:

• Define approaches for evidence architecture, language architecture, ontology design, and machine-readable content standards.
• Drive creation of reusable authority hubs, narrative frameworks, taxonomy standards, and metadata structures supporting AI retrieval.
• Partner with Medical, Corporate Communications, and Commercial organizations to align evidence planning with AI discovery requirements.
• Shape business and technical requirements for the platforms, content models, data structures, and digital experiences needed to improve machine understanding.

AI Visibility & Measurement:

• Build enterprise capabilities for monitoring AI visibility, citation quality, narrative accuracy, authority signals, and competitive positioning.
• Establish ongoing monitoring, assessment, remediation, and governance processes.
• Lead evaluation and implementation of AI visibility and GEO measurement platforms.

Team Leadership & Organizational Development:

• Recruit, develop, and lead a high-performing team across strategy, ontology, evidence architecture, technical discoverability, GEO operations, and insights.
• Lead a distributed, high-performing team across strategy and brand engagement, technical discoverability, and monitoring and insights operations.
• Define capability requirements and workforce strategies needed to scale AI Discoverability globally.
• Develop new centers of excellence and communities of practice focused on AI-mediated discovery.
• Establish partnerships with external experts, agencies, platforms, and emerging AI ecosystem providers.

Qualifications

Required:

• Bachelor’s degree (BA/BS).
• 10+ years leading enterprise digital, product, content, search, AI, analytics, or customer experience initiatives.
• Experience translating rapidly evolving technologies into business strategies, investment roadmaps, scalable services, and measurable outcomes.
• Proven ability to lead through influence in highly matrixed environments spanning business, medical, communications, data, technology, digital, and governance functions.
• Systems thinking across people, process, technology, and partner ecosystems
• Strong technical foundation in AI/ML, including GenAI and agentic AI concepts, with the ability to understand capabilities, constraint…