Senior Manager, AITO AI Platform & Foundation

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.

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.

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.

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.