Level

Pfizer

AI Transformation Office Head

Pfizer is hiring an AI Transformation Office Head in Shanghai, China. Level rates it ; you can apply on Pfizer.

Level's read on this job

  • On Level's scale, this role is Works on AI ●●●○: the daily work is on AI products, without building the model.
  • The posting mentions RAG and MLOps among its tools and skills.
  • Level classes it as a senior role.
  • Pfizer has 567 other open roles on Level.
  • Posted in the last few days.

AI in this role

ragml-ops

1. Role Summary

The AI Transformation Office Head owns Pfizer China’s AI transformation agenda and brings China’s AI capability into one lean, flat office. The role aligns AI strategy, portfolio, value and adoption with commercial priorities, owns the China AI platform and LLM foundation, and leads rapid AI build through a dedicated AI engineering pool. The AITO Head decides what AI is worth doing, proves value quickly in PO-led PODs, and hands proven solutions to Digital & Technology (D&T) to scale and run.

2. Key Accountabilities

AI Strategy & Portfolio

  • Land China’s AI strategy and ensure alignment with International AIT priorities and enterprise standards.
  • Own the AI portfolio: intake, prioritization, funding gates, and scale / stop decisions, maintained in a single, prioritized backlog against clear value criteria.

Value & Investment

  • Own the business case, KPIs and benefits realization for AI investments, including model-cost economics, supported by the AIT Value & Performance Lead and the AIT Portfolio PMO.
  • Co-own, with GTMx, the build / buy / partner recommendation and ecosystem judgement for AI solutions.

AI Product & Rapid Build

  • Lead the AI Product Owners directly; run each AI product as a PO-led POD with a single business outcome owner, one PO from MVP to scale, D&T engaged from MVP, and a BAU owner agreed before scale.
  • Lead, through the AIT Acceleration Lead (Principal Engineer), the AI engineering pool and Forward Deployment Engineering (FDE) for rapid prototyping, solution build, small language models and the AICL AI layer, flexing with matrixed PIC and contractor capacity.

AI Platform & Foundation

  • Own, through the AI Platform & Foundation Director, the China AI platform and China LLM foundation — architecture, cloud engineering, model onboarding and qualification, and the production release gate — as the single AITO interface with Corporate and Global CIO teams.
  • Make localize-versus-build decisions for global platform capabilities, re-use global patterns before local build, and bring China-proven capabilities back for global reuse.
  • Own AI layer of the AI Empowered Consumption Layer (AICL) and ensure it is delivered as one POD.

Adoption & China-for-Global

  • Partner with GTMx, which leads AI fluency, champions, change and adoption, so that validated AI products land in the business; support builder adoption of the China AI platform.
  • Grow the China-for-Global reusable AI offering — turn China-proven solutions into reusable assets, make the value case for global reuse, and drive adopt / adapt / decline decisions with International AIT.

3. Required Capabilities & Competencies

(a) Technical Competency & Experience

  • AI-native leadership with hands-on fluency and technical depth — able to credibly challenge feasibility, model choice, cost and reuse.
  • Deep experience with LLMs and agentic AI: prompt / RAG, agent workflows, evaluation, guardrails, and enterprise-grade deployment.
  • Working knowledge of AI platform and cloud architecture on China cloud providers, LLM foundation and MLOps / LLMOps, and China generative AI compliance (PIPL, CAC rules), sufficient to govern platform choices with Corporate and Global CIO teams.
  • AI portfolio and value management, including model-cost / cost-per-outcome discipline.
  • Product management and rapid experimentation at scale — leading product owners and engineering teams to move ideas from concept to validated MVP.
  • Experience deploying AI in real commercial scenarios, ideally including China ecosystem contexts (e.g. WeChat / enterprise assistants, local model options).
  • Able to bring large-scale technology / internet-industry AI innovation experience into a commercial pharma organization.
  • 12+ years in AI / digital, with 5+ years leading AI or advanced-analytics teams; proven delivery of AI products into real business use.
  • Track record of AI strategy, portfolio and value ownership — accountable for impact, not only prototypes.
  • Experience influencing senior business, technology, legal / compliance and market stakeholders in a matrix, without relying solely on direct authority.
  • Master's or PhD in a technical or quantitative discipline (e.g. Computer Science, AI / Machine Learning, Data Science, Engineering) preferred; equivalent experience considered.
  • Regulated-industry experience (tech giants / biopharma / healthcare / finance, etc.) an advantage but not required if AI leadership depth is strong.
  • Fluent Mandarin and professional English for global collaboration.

(b) Leadership Competencies

  • Business Acumen — connects AI choices to clear commercial value and business priorities.
  • Leads Change — mobilizes the organization toward AI-native ways of working.
  • Acts Decisively — makes timely scale / stop calls under uncertainty.
  • Builds Effective Teams — attracts, develops and leads a high-performing, lean and flat AI team of product, engineering and platform talent.

4. Key Collaboration

This is a leadership role within China CEI, reporting to the CEI Head. The AITO Head leads the AI Platform & Foundation Director, the AIT Acceleration Lead (Principal Engineer), the AI Product Owners, the AIT Value & Performance Lead and the AIT Portfolio PMO, and directs matrixed PIC and contractor capacity. The role operates through a senior matrix across peer teams: GTMx (Demand & Adopt) for demand shaping, AI fluency and adoption; Digital & Technology (D&T, Scale & Run) for data, enterprise engineering, production and BAU; the Pfizer Innovation Center (PIC, Build & Package) for flexible delivery and reusable-asset packaging; and Global Commercial Analytics (GCA), including GCA DSM for AICL business definitions and unified KPIs. It partners with International AIT and the Corporate and Global CIO, and with Legal, Privacy, Risk, Compliance, Security, Procurement and the China Data Protection Office (DPO).

5. Measures of Success

  • Prioritized AI use cases progressed from a single, value-ranked backlog to validated MVP and production, each run as a PO-led POD with a named business owner and a clear scale / stop decision.
  • Measurable value realization against business cases, with disciplined model-cost / cost-per-outcome economics.
  • Faster, reliable progression from concept to validated MVP (0→1), and clean handover to D&T with a BAU owner agreed before scale.
  • A secure, compliant and cost-transparent China AI platform and LLM foundation, aligned with Corporate and Global CIO standards and free of fragmented local builds.
  • AICL delivered as one POD across GCA DSM, AITO and D&T, with unified KPI definitions and reuse across use cases.
  • Growth of the China-for-Global reusable AI offering, evidenced by reusable assets and adopt / adapt / decline decisions with International AIT.

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.

 

 

Information & Business Tech

How we rate this

AI Transformation Office Head at Pfizer rates 74 out of 100 for how much of the daily work is AI. That makes it Works on AI (AI Level 3 of 4). The level is about AI in the job, not seniority.

Classification

Works on AI. The daily work is on AI products, without building the model.

  1. ●●●● Builds AI80 to 100
  2. ●●●○ Works on AI60 to 79
  3. ●●○○ Uses AI40 to 59
  4. ●○○○ Little AI0 to 39

Levels come from how often the tools, models and workflows of the role are named in the posting itself. Read the description and count the AI tools, models and workflows it names.

Prepare for this job

Built from this posting and from similar jobs on Level.

Skills and AI tools this role asks for

RAGML Ops

Questions you could be asked

  1. How would you design a retrieval step so the model answers from real data instead of guessing?
  2. How do you monitor a model once it's live, and how do you know it needs retraining?
  3. Describe a typical day in a role like this one: which parts run through AI directly?
  4. If you removed AI from this role, what would be left, and how do you decide what still needs a human?

Adapt your resume

  • List these exact terms on your resume: RAG and ML Ops. An applicant tracking system matches the wording, not the idea.
  • Attach one line of real, concrete experience to at least one of them. A tool named with nothing behind it rarely survives a human read.
  • Show where AI is part of your daily process, not a one-off project. This role expects it to be a running habit.

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