Senior Manager, AI Platform – Foundation

Pfizer

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

Posted 11/11/2026full-timeShanghai • ChinaSeniorWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in AI platform and cloud engineering, including model serving and lifecycle management, while ensuring compliance with industry regulations and standards. Proven ability to lead cross-functional teams and manage complex projects in a matrixed environment.

Highest-signal resume keywords

AI Platform EngineeringCloud EngineeringModel Lifecycle ManagementCI/CD and Infrastructure as CodeRegulatory Compliance Knowledge

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

Model ServingAI GatewayContainersKubernetesIdentity and Access ManagementAI Development ToolchainModel QualificationPre-Production EvaluationCloud Cost ControlObservability

Soft Skills

MentoringStakeholder EngagementCross-Functional Collaboration

Tools & Technologies

Tencent CloudAlibaba CloudAI ServicesAgent Frameworks

Industry Keywords

PIPLCAC Generative AI RulesMLPSPharmaceutical IndustryData Protection

Tech Stack

Tools & technologies

CloudKubernetes

About the role

Key responsibilities & impact

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, including 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
Lead and govern the China LLM foundation, including model selection, onboarding, qualification, evaluation, version and lifecycle management
Lead and govern the AI platform technical qualification gate for models, services and tools
Liaise with Corporate and Global CIO on AI platform, cloud, security and architecture requirements and global roadmap visibility
Lead platform-level operations including on-call, incident response, runbooks, platform reliability, service health, and model, token and cost reporting
Set and enforce platform-level engineering standards, including reference architectures, CI/CD, infrastructure as code, code review and documentation
Manage risks, dependencies, capacity and vendor deliverables
Mentor Managers, engineers and contractors
Align the AI platform technical qualification gate with production-readiness and go-live gates
Direct matrixed PIC and contractor capacity and engage governance, procurement, legal, compliance, data protection and cloud vendor stakeholders

Requirements

What you’ll need

AI platform and cloud engineering experience, including 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 experience, including model qualification, pre-production evaluation (safety, content compliance and performance) and lifecycle management
Production service operation, observability, cloud cost control, security and privacy review
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; a master’s or doctoral degree may reduce the years required
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