Director, AI Engineering & Platforms

ROLE SUMMARY 

The Director, AI Engineering & Platforms reports directly to the AI Strategy & Realization Lead within PGS Data, Analytics & AI Transformation and is responsible for the the AI model strategy, costing, platform, and coding standards that AI application use cases are built on across the AI Strategy & Realization team and the broader Data, Analytics & AI Transformation organization, leading a dedicated engineering bench that ships and scales AI applications across PGS. 

This individual establishes rigorous model evaluation and vetting practices, assessing candidate AI models against performance, cost, safety, and Responsible AI criteria before they are cleared for use, and defines costing models fit for purpose for AI use cases and standards so PGS can make sound build, buy, and model-selection decisions. The role keeps PGS’s technical direction aligned with the enterprise by partnering with Digital on engineering standards and AI models, including active participation in the Data Readiness and AI Engineering guilds. 

Working in close step with the AI Product, Innovation & Emerging Technology tower and the AI Capabilities & Enablement tower, this leader carries use cases from prototype to MVP and beyond, and partners with Digital to scale larger, more complex programs once they’ve proven their value. Leading a team, this role builds the engineering foundation that turns PGS’s AI ambitions into reality. 

ROLE RESPONSIBILITIES 

• Define and own the model strategy, costing, platform, and coding standards that govern how AI application use cases are built across the AI Strategy & Realization team and the broader Data, Analytics & AI Transformation organization.

• Lead a specialized AI engineering team that ships and scales AI application use cases where appropriate, holding delivery to a consistent, production-grade technical bar.

• Establish AI model framework evaluation and vetting processes, assessing candidate models against performance, cost, safety, and Responsible AI criteria before they are approved for use across PGS.

• Define costing models fit for purpose for AI use cases and standards, giving PGS leaders a consistent, defensible basis for build, buy, and model-selection decisions.

• Partner with Digital on engineering standards and AI models, including active participation in the Data Readiness and AI Engineering guilds, to keep PGS’s technical approach aligned with enterprise direction.

• Drive collaboration with the AI Product, Innovation & Emerging Technology tower and the AI Capabilities & Enablement tower to carry use cases from prototype to MVP and beyond.

• Partner with Digital to scale larger, complex programs once use cases have proven their value, ensuring a clean handoff to enterprise-scale platforms and support models.

• Lead, develop, and grow a team, including performance management, coaching, and career development, while building an inclusive, high-performing engineering culture.

• Establish engineering health and quality metrics covering model performance, cost efficiency, and reliability.

BASIC QUALIFICATIONS 

• Bachelor’s degree in Computer Science, Engineering, Information Systems, or a related field with at least 8 years of relevant experience; OR a master’s degree with at least 7 years of experience.

• Demonstrated significant experience leading AI/ML engineering teams, including setting technical architecture, coding, and delivery standards for production-grade AI applications.

• Proven success building and running model evaluation, vetting, or validation processes, assessing AI models against performance, cost, safety, and responsible AI criteria.

• Demonstrated experience developing costing models and frameworks for technology or AI initiatives that inform build, buy, and model-selection decisions.

• People leadership experience managing engineering teams of meaningful scale, including hiring, coaching, and performance management.

• Demonstrated ability to partner effectively with enterprise Digital/technology organizations, including guild or standards-body participation, to align technical direction across a large, matrixed organization.

• Excellent stakeholder management and communication skills, with the ability to translate technical standards into clear guidance for both engineering and business audiences.

PREFERRED QUALIFICATIONS 

• Strong Pfizer colleague network, particularly across PGS, Digital, and Data, Anal…