Director, AI Readiness

ROLE SUMMARY

Pfizer Global Supply (PGS) is transforming how data powers its end-to-end supply network.

The Director, AI Data Readiness & Knowledge Engineering lead drives PGS's Unified Data & Knowledge Strategy — connecting structured data with semi-structured and unstructured knowledge — to deliver trusted, AI-ready assets that power analytics, applications, AI, and agent-enabled capabilities across PGS. Reporting to the Data Engineering Lead, this role owns the Knowledge Engineering, Ontology & Semantic Enablement team, defining the technology roadmap and platform strategy for unstructured and semi-structured knowledge — including knowledge graphs, vector stores, and RAG infrastructure — and serving as business owner for the semantic and knowledge layer of the PGS common data model. The role ensures both regulated content (SOPs, GWIs, quality and manufacturing documentation) and broader supply chain knowledge materials are trusted and AI-consumable, and partners with the Data Engineering Lead, Enterprise Analytics, Data Governance, and Digital to prioritize scope, drive adoption, and deliver measurable business outcomes.

ROLE RESPONSIBILITIES
• Define and own the PGS AI Data Readiness and Knowledge Engineering strategy, establishing how structured data, unstructured information, semantic context, and enterprise knowledge will be made trusted, reusable, and consumable by users, analytics, applications, and agents.
• Set the business vision and engineering roadmap for the PGS semantic and knowledge foundation, including business glossaries, taxonomies, metrics, ontologies, semantic models, knowledge graphs, vectorized knowledge assets, and contextual retrieval.
• Lead selected enterprise engineering capabilities and reference implementations for RAG, semantic retrieval, AI search, knowledge grounding, agent access, and application consumption where common ownership is necessary to achieve consistency and reuse.
• Establish the federated engineering model for AI-ready data and knowledge, defining which capabilities are delivered centrally and which are delivered by domain teams using common standards, reusable services, technical playbooks, and certification requirements.
• Create standards and reusable patterns for ingestion, contextualization, chunking, vectorization, indexing, retrieval, reranking, grounding, citations, evaluation, observability, security, and traceability across structured and unstructured AI solutions.
• Define the enterprise approach for agent-ready information access, including governed Model Context Protocol (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 and enable consistent consumption across analytics, Digital applications, and AI solutions.
• Co-partner with Digital leadership on architecture, technology selection, platform engineering, production deployment, scalability, security, operations, and modernization while retaining business ownership of priorities, standards, adoption, engineering capability outcomes, and value realization.
• Own and operationalize the PGS AI Data Readiness framework and scorecard, measuring data-product readiness, semantic maturity, knowledge connectivity, retrieval quality, agent readiness, adoption, reuse, and business impact.
• Build technical capability across PGS by mentoring engineering teams, leading design reviews, accelerating high-value prototypes, and creating communities of practice around AI-ready data, semantic technologies, and knowledge engineering.

BASIC QUALIFICATIONS
• Applicant must have a bachelor’s degree in computer science, data science, information systems, engineering, analytics, or a related field with at least 8 years of relevant experience in enterprise data, AI engineering, software engineering, data platforms, analytics, or architecture; OR a master’s degree with at least 7 years of relevant experience; OR a PhD with at least 5 years of relevant experience.
• Demonstrated 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.
• Demonstrated 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.
• Demonstrated ability to influence senior business and technology leaders, resolve complex cross-functional decisions, and communicate strategy, trade-offs, risk, progress, and value.

PREFERRED QUALIFICATIONS
• Advanced degree in a relevant discipline.
• Experience with enterprise semantic layers, business glossaries, taxonomies, metrics layers, ontologies, knowledge graphs, semantic search, and knowledge platforms.
• Experience with embedding generation, chunking, vectorization, indexing, retrieval, reranking, grounding, evaluation, citations, and AI observability.
• Experience with AI agents, MCP, reusable agent skills, tool-access patterns, multi-agent ecosystems, or application consumption of governed enterprise data and knowledge.
• Experience with Snowflake, Cortex Search, Cortex Analyst, cloud-native platforms, microservices, APIs, or enterprise AI platforms.
• Experience defining AI readiness maturity models, certification standards, scorecards, executive dashboards, and value-realization measures.
• 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.
• Demonstrated success mentoring engineers and building communities of practice that scale common capabilities across federated teams.

PHYSICAL/MENTAL REQUIREMENTS

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 where requirements may be incomplete or competing.

NON-STANDARD WORK SCHEDULE, TRAVEL OR ENVIRONMENT REQUIREMENTS

This is a global role requiring collaboration across time zones. Periodic domestic and international travel may be required based on business need. Occasional participation outside standard local working hours may be necessary to support global strategy sessions, design reviews, critical prototypes, architecture decisions, or delivery activities.

OTHER INFORMATION

Last Date to Apply: October 28, 2026

The annual base salary for this position ranges from $162,900.00 to $271,500.00. In addition, this position is eligible for participation in Pfizer’s Global Performance Plan with a bonus target of 20.0% of the base salary and eligibility to participate in our share based long term incentive program. We offer comprehensive and generous benefits and programs to help our colleagues lead healthy lives and to support each of life’s moments. Benefits offered include a 401(k) plan with Pfizer Matching Contributions and an additional Pfizer Retirement Savings Contribution, paid vacation, holiday and personal days, paid caregiver/parental and medical leave, and health benefits to include medical, prescription drug, dental and vision coverage. Learn more at Pfizer Candidate Site – U.S. Benefits | (uscandidates.mypfizerbenefits.com). Pfizer compensation structures and benefit packages are aligned based on the location of hire. The United States salary range provided does not apply to Tampa, FL or any location outside of the United States.

This role is posted in multiple locations. If you are applying for the role in an secondary job posting location where pay transparency regulations apply, your Talent Advisor will share the local pay information with you during the first interview.

Relocation assistance may be available based on business needs and/or eligibility.

Candidates must be authorized to be employed in the U.S. by any employer.

U.S. work visa sponsorship (such as TN, O-1, H-1B, etc.) is not available for this role now or in the future.

To learn more about acceptable and prohibited uses of AI during the recruitment process, please review our candidate AI-use guidelines available on Pfizer Careers.

Information & Business Tech

About Us

A career at Pfizer offers opportunity, ownership and impact.

All over the world, Pfizer colleagues work together to positively impact health for everyone, everywhere. Our colleagues have the opportunity to grow and develop a career that offers both individual and company success; be part of an ownership culture that values diversity and where all colleagues are energized and engaged; and the ability to impact the health and lives of millions of people. Pfizer, a global leader in the bio pharmaceutical industry, is continuously seeking top talent who are inspired by our purpose to innovate to bring therapies to patients that significantly improve their lives.