1. Role Summary
The Director owns the China AI platform and the China LLM foundation end to end – architecture, engineering, security and compliance, release management, roadmap and budget. The platform gives Pfizer China teams governed access to locally available large language models (for example Qwen, DeepSeek, Kimi and GLM) on China cloud providers, with an AI gateway and guardrails, separate innovation and production environments, and model and agent tooling on top. Its users are business analysts, data scientists and engineers across Pfizer China Commercial. Self-hosting of open-weight models may be a future requirement.
The role is the single AITO interface with Corporate and Global CIO teams on the AI platform, makes China requirements visible to Global, re-uses global patterns before local build to avoid fragmentation, and runs the AI platform release gate. This is a hands-on leadership role: in the first year, the Director stands up and runs the China cloud environments and AI platform while building the AI platform team.
2. Key Accountabilities
- Own the China AI platform end to end: architecture, engineering, security and compliance, release management, product roadmap and budget for licenses and infrastructure; maintain the roadmap with China business stakeholders and CIO platform teams, and decide which global platform capabilities are localized and which need a China-built equivalent.
- Own cloud platform engineering on China cloud providers (Tencent Cloud, Alibaba Cloud, AWS China): environments, identity and access management, GPU capacity, model serving and deployment, monitoring, automation and infrastructure as code.
- Own and manage the China LLM foundation: model selection, qualification, evaluation, version and lifecycle management, providing the model and platform layer on which the AI layer of the AI Empowered Consumption Layer (AICL) and China AI solutions are built; plan for self-hosting of open-weight models as a future option.
- Lead onboarding and qualification of new models, cloud services and tools – security, privacy (including China data residency under PIPL), legal and China generative AI compliance – following global guidelines, and keep the platform inventory current.
- Set AI platform and engineering standards: reference architectures, reusable patterns and non-functional requirements for model integration, agent runtime, guardrails, evaluation and MLOps / LLMOps, and engineering practices (code review, CI/CD, infrastructure as code, documentation).
- Act as the single AITO interface with Corporate and Global CIO teams on the AI platform and its cloud, security and architecture requirements; represent China in global platform roadmaps, re-use global patterns (gateway, guardrails, observability, agent frameworks) where they apply, and bring China-proven capabilities back for global reuse.
- Run the AI platform release gate that controls which models, services and AI components move from the innovation environment to production, aligned with the D&T go-live gate for business solutions.
- Run the AI platform as a service: in-region on-call and incident response with escalation to global teams, runbooks, and reporting of service health, model and token utilization and cost into Pfizer’s global AI dashboards.
- Work with Procurement, Legal, Compliance, Cybersecurity and the China Data Protection Office (DPO) so the platform operates within guardrails, and manage cloud and software license vendors.
- Support builder adoption with China business teams and engineers through sample agents, reusable components, documentation, training and an active user community, in step with GTMx AI fluency and enablement programs.
- Lead and develop the AI platform team of colleagues and contractors, plus matrixed PIC capacity: set engineering standards (code review, CI/CD, infrastructure as code, documentation), hold the team to them, mentor engineers and stay hands-on to fill gaps.
3. Required Capabilities & Competencies
(a) Critical Capabilities & Qualifications
- AI platform engineering and technical product leadership, with production experience of model serving or Model as a Service (MaaS) integration, an AI gateway, guardrails or content moderation, and at least one agent framework.
- Cloud platform engineering on at least one major cloud (Alibaba Cloud, Tencent Cloud or AWS): containers and Kubernetes, identity and access management, GPU capacity, infrastructure as code and CI/CD; writes production-quality Python and is comfortable with Linux and Git.
- LLM foundation management: model selection, pre-production evaluation (safety, content compliance and performance) and lifecycle management.
- Has run a production service to service level agreements (SLAs): monitoring and observability, on-call, incident management and cloud cost control.
- Has taken new technology through enterprise security, privacy and architecture review before production use.
- Proven partnership with Corporate or Global CIO organizations, and experience managing technology suppliers, including cloud hosting and software license agreements.
- Bachelor’s degree or above in Computer Science, Software Engineering, Artificial Intelligence or a closely related discipline.
- Typically 12+ years of professional experience, including 5+ years hands-on building and running production cloud, data or AI platforms and experience hiring, leading and developing engineers, including contractors. Candidates with an exceptional background may be considered from 10+ years.
- Professional working proficiency in Mandarin and English.
- Preferred: working knowledge of the Personal Information Protection Law (PIPL), the Cyberspace Administration of China (CAC) rules for generative AI services and the Multi-Level Protection Scheme (MLPS); experience serving open-weight models on GPU infrastructure (domestic accelerators a plus); enterprise single sign-on (SAML/OIDC) and cloud IAM integration; experience in a multinational working with global platform, security and governance teams across time zones; pharmaceutical or other regulated industry experience.
(b) Leadership Expectations
- Outcome ownership: connects platform 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 peer teams and partners.
- Precision and learning: communicates technical decisions and trade-offs clearly to senior business and technology leaders, uses evidence and telemetry and continuously improves the service.
- Hands-on and resilient: stays close to the engineering, keeps digging into hard technical problems until the root cause is understood, and grows platform engineering talent.
4. Key Collaboration
The Director works within AITO under the AITO Head and partners closely with the AIT Acceleration Lead, whose engineering team builds AI solutions, small language models and the AICL AI layer on the platform. The role works with D&T Data Engineering & Semantics, which owns the AICL data (CL) layer, and with GCA DSM, which owns AICL business definitions and unified KPIs, delivering AICL as one POD. It agrees the production boundary with D&T Enterprise Engineering, Deployment & Operations, which runs the business applications built on the platform, aligns the AI platform release gate with the D&T go-live gate, and directs matrixed PIC and contractor capacity. Externally to CEI, the role is the primary AITO interface with Corporate and Global CIO platform, cloud hosting, cybersecurity and AI governance teams, and works with Procurement, Legal, Compliance, the China Data Protection Office (DPO) and technology vendors including Alibaba Cloud and Tencent Cloud.
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 a documented qualification and AI platform release gate.
- Clear alignment with Corporate and Global CIO standards: global patterns re-used, China requirements on the global roadmap, and no fragmented local platforms.
- Clear localize-versus-build decisions, with China-proven capabilities contributed back for global reuse.
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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