Senior Manager, AI Platform & Foundation

 Role Summary

The Senior Manager is a capability leader within AITO AI Platform & Foundation, owning one or more capability areas — including the Corporate & Global CIO liaison — while retaining sufficient breadth to lead across the China AI platform and LLM foundation.

The role combines senior technical leadership with hands-on direction of platform engineering, model qualification, release management and service operation, so that AI builders across Pfizer China Commercial work on one governed, secure and cost-transparent platform.

2. Key Accountabilities

• Own one or more team capability areas end to end, including roadmap, standards, delivery, controls, service levels and lifecycle outcomes.

• Lead and govern China AI platform engineering — AI gateway, guardrails, agent runtime, AI development toolchain, reusable AI services, and separate innovation and production environments.

• Lead and govern cloud platform engineering on approved China cloud environments, including Tencent Cloud and Alibaba Cloud, and other approved providers as applicable — environments, identity and access management, GPU capacity, model serving, monitoring and infrastructure as code.

• Lead and govern the China LLM foundation — model selection, onboarding, qualification, evaluation, version and lifecycle management — and the AI platform technical qualification gate for models, services and tools.

• Lead and govern Corporate & Global CIO liaison — AI platform, cloud, security and architecture requirements, re-use of global patterns and visibility of China requirements on global roadmaps.

• Lead and govern platform-level operations — on-call, incident response, runbooks, platform reliability, service health, and model, token and cost reporting.

• Set and enforce platform-level engineering standards — AI platform reference architectures, platform CI/CD, infrastructure as code, code review and documentation — and support localize-versus-build decisions.

• Manage material risks, dependencies, capacity and vendor deliverables, and mentor Managers, engineers and contractors.

3. Required Capabilities & Competencies

(a) Critical Capabilities & Qualifications

• AI platform and cloud engineering: model serving or Model as a Service (MaaS) integration, AI gateway, guardrails, agent frameworks, containers and Kubernetes, identity and access management, infrastructure as code and CI/CD.

• LLM foundation management: model qualification, pre-production evaluation (safety, content compliance and performance) and lifecycle management.

• Production service operation, observability, cloud cost control, security and privacy review, and working knowledge of PIPL, CAC generative AI rules and MLPS.

• Bachelor’s degree or above in Computer Science, Software Engineering, Artificial Intelligence or a related computing discipline.

• 10+ years of progressive relevant experience based on a bachelor’s degree, where a master’s or doctoral degree may reduce the years required, with scope and judgment consistent with this role.

• Demonstrated ability to work across business, product, technology, data and governance stakeholders in a matrixed environment.

• Experience in the pharmaceutical or another highly regulated industry, and the China technology, data, privacy or vendor environment, is preferred.

(b) Leadership Expectations

• Outcome ownership: connects decisions to measurable business, user, service and transformation outcomes.

• AI-first and enterprise-minded: applies responsible AI, reuse, architecture, security, privacy and scale principles appropriate to the work.

• POD collaboration: enables clear accountability, effective cross-functional execution and minimal handoff friction across the AI engineering pool, D&T, PIC, Corporate and Global CIO teams and governance partners.

• Precision and learning: communicates clearly, documents decisions, uses evidence and telemetry and continuously improves delivery.

4. Key Collaboration

aligns the AI platform technical qualification gate with the production-readiness and go-live gate run by D&T Enterprise Engineering, Deployment & Operations, and directs matrixed PIC and contractor capacity. Outside CEI, it engages Corporate and Global CIO platform, cloud hosting, cybersecurity and AI governance teams, Procurement, Legal, Compliance, the China Data Protection Office (DPO) and cloud vendors.

5. Measures of Success

• A secure, compliant and cost-transparent China AI platform and LLM foundation, running to agreed service levels.

• Every new model, service and tool onboarded through documented qualification and the AI platform technical qualification gate.

• Global patterns re-used, China requirements visible on global roadmaps and no fragmented local platforms.

• Reusable platform services and components adopted by AI engineers and builders across China Commercial.

Pfizer is an equal opportunity employer and complies with all applicable equal employment opportunity legislation in each jurisdiction in which it operates.

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.

 

 

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