Director, AI Readiness

Pfizer

. Define and own the PGS AI Data Readiness and Knowledge Engineering strategy .

Posted 10/21/2026full-timeUnited StatesLead💰 $162,900 - $271,500 per yearWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in defining and operationalizing AI Data Readiness strategies, leading enterprise engineering capabilities, and establishing standards for AI-ready data and knowledge. Proficient in semantic retrieval, knowledge engineering, and influencing cross-functional teams to achieve measurable business outcomes.

Highest-signal resume keywords

AI Data Readiness StrategySemantic RetrievalKnowledge EngineeringEnterprise Data GovernanceMentoring Engineering Teams

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

AI-Enabled ApplicationsSemantic ModelingKnowledge GraphsVectorizationData QualityData LineageRAG PatternsEvaluation MetricsAgent-Consumption PatternsEmbedding Generation

Soft Skills

Influencing Senior LeadersComplex Problem SolvingEffective CommunicationMentoringCollaboration

Tools & Technologies

SnowflakeCortex SearchCortex AnalystCloud-Native PlatformsMicroservicesAPIsEnterprise AI Platforms

Industry Keywords

Pharmaceutical ManufacturingSupply ChainQuality ProcessesCommercial ProcessesResponsible AI

Tech Stack

Tools & technologies

CloudCyber SecurityMicroservices

About the role

Key responsibilities & impact

Define and own the PGS AI Data Readiness and Knowledge Engineering strategy
Set the business vision and engineering roadmap for the PGS semantic and knowledge foundation
Lead enterprise engineering capabilities and reference implementations for RAG, semantic retrieval, AI search, knowledge grounding, agent access, and application consumption
Establish the federated engineering model for AI-ready data and knowledge
Create standards and reusable patterns for ingestion, contextualization, chunking, vectorization, indexing, retrieval, reranking, grounding, citations, evaluation, observability, security, and traceability
Define the enterprise approach for agent-ready information access, including governed MCP patterns, reusable agent skills, semantic interfaces, and access to certified data products and knowledge assets
Partner with Enterprise Analytics and data-product teams to align the semantic and knowledge strategy with the PGS common data model
Co-partner with Digital leadership on architecture, technology selection, platform engineering, production deployment, scalability, security, operations, and modernization
Own and operationalize the PGS AI Data Readiness framework and scorecard
Measure data-product readiness, semantic maturity, knowledge connectivity, retrieval quality, agent readiness, adoption, reuse, and business impact
Mentor engineering teams, lead design reviews, accelerate high-value prototypes, and create communities of practice
Collaborate across global time zones and travel domestically and internationally as needed

Requirements

What you’ll need

Bachelor’s degree in computer science, data science, information systems, engineering, analytics, or a related field with at least 8 years of relevant experience; OR a master’s degree with at least 7 years of relevant experience; OR a PhD with at least 5 years of relevant experience
Experience defining enterprise data, AI, semantic, knowledge, or platform strategies and translating them into funded roadmaps, engineering capabilities, adoption, and measurable business outcomes
Deep technical experience building AI-enabled applications using structured data, unstructured content, vectorized information, semantic retrieval, or RAG patterns
Strong understanding of data products, metadata, lineage, data quality, governance, semantic modeling, ontologies, knowledge graphs, vector stores, retrieval, evaluation, and agent-consumption patterns
Experience leading selected engineering capabilities, reference implementations, reusable frameworks, or shared services within a federated delivery model
Experience establishing standards for AI-ready data and knowledge, including trust, explainability, traceability, security, observability, and Responsible AI considerations
Ability to influence senior business and technology leaders, resolve complex cross-functional decisions, and communicate strategy, trade-offs, risk, progress, and value
Must be authorized to be employed in the U.S. by any employer
Permanent work authorization in the United States required
U.S. work visa sponsorship is not available now or in the future
Advanced degree in a relevant discipline preferred
Preferred experience with enterprise semantic layers, business glossaries, taxonomies, metrics layers, ontologies, knowledge graphs, semantic search, and knowledge platforms
Preferred experience with embedding generation, chunking, vectorization, indexing, retrieval, reranking, grounding, evaluation, citations, and AI observability
Preferred experience with AI agents, MCP, reusable agent skills, tool-access patterns, multi-agent ecosystems, or governed enterprise data and knowledge consumption
Preferred experience with Snowflake, Cortex Search, Cortex Analyst, cloud-native platforms, microservices, APIs, or enterprise AI platforms
Preferred experience defining AI readiness maturity models, certification standards, scorecards, executive dashboards, and value-realization measures
Preferred experience partnering across business, Enterprise Analytics, Digital, architecture, engineering, data governance, cybersecurity, privacy, and Responsible AI teams
Knowledge of pharmaceutical manufacturing, supply chain, quality, and commercial processes preferred
Demonstrated success mentoring engineers and building communities of practice preferred
Ability to perform complex analysis and exercise sound judgment across interdependent business, data, AI, semantic, architecture, engineering, governance, and technology considerations
Ability to sustain focused review of detailed strategies, technical designs, evaluations, readiness measures, risks, and investment choices

Benefits

Comp & perks

Global Performance Plan with a bonus target of 20.0% of base salary
Share based long term incentive program
401(k) plan with Pfizer Matching Contributions
Additional Pfizer Retirement Savings Contribution
Paid vacation, holiday and personal days
Paid caregiver/parental and medical leave
Medical, prescription drug, dental and vision coverage
Relocation assistance may be available based on business needs and/or eligibility