Forward Deployment Manager - Information & Business Tech

. Role Summary

The Forward Deployment Engineer (FDE) owns the how — building working AI solutions fast. Within the AITO AI engineering pool, the role turns prioritized ideas and product requirements into hands-on prototypes, proofs of concept and validated minimum viable products, proving technical feasibility for flagship AI opportunities (0→1).

Working side by side with the AI Product Owner in a PO-led POD, the engineer designs, builds, integrates and evaluates AI and agentic solutions on the China AI platform, contributes to small language models and the AI layer of the AI Empowered Consumption Layer (AICL), and hands validated work to Digital & Technology (D&T) and PIC for production, scale and sustainable ownership.

2. Key Accountabilities

• Design, build and integrate AI and agentic solutions — rapid prototypes, proofs of concept and validated MVPs — for high-value opportunities.

• Engineer agentic applications and RAG pipelines: retrieval, model and API integration, orchestration, prompt and context engineering, and human-in-the-loop workflows, using China AI platform reference architectures and guardrails.

• Contribute to small language model and domain model development — data preparation, fine-tuning, distillation and evaluation — deployed through the China LLM foundation and AI platform release gate.

• Build the AICL AI layer (agents, retrieval and orchestration) as one POD with the D&T Data Engineering & Semantics team (CL layer) and GCA DSM (business definitions and unified KPIs).

• Build evaluation, testing and guardrails to prove feasibility, quality and safety before scale.

• Partner daily with the AI Product Owner to translate requirements into working solutions and iterate on feedback; surface constraints, effort and risk early to inform scale or stop decisions.

• Prepare clean, documented handovers to D&T and PIC, including architecture notes, evaluation evidence and known limitations.

• Apply model-cost / cost-per-outcome awareness in design and model choices.

• Contribute reusable patterns, components and sample agents to the China AI platform and builder community.

3. Required Capabilities & Competencies

• Hands-on AI / software engineering: rapid prototyping, applied development and integration of AI and agentic solutions; production-quality Python.

• Agentic and RAG engineering: embeddings, re-rankers, vector databases, model and API integration, orchestration, prompt and context engineering, evaluation and guardrails.

• Working knowledge of small language model fine-tuning and evaluation, MLOps and LLMOps, CI/CD and secure, privacy-aware deployment.

• Model-cost / cost-per-outcome awareness and pragmatic engineering trade-offs.

• Builder mindset: ships working solutions fast with rigor, curiosity and pragmatic engineering judgment, with strong cross-functional collaboration.

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

• 8+ years of relevant technology experience, including 5+ years of hands-on software, data or AI engineering experience and demonstrated delivery of AI/ML or agentic solutions.

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

4. Key Collaboration

The role works in the AITO AI engineering pool under the AIT Acceleration Lead, partnering daily with the AI Product Owner in a PO-led POD. It builds on the China AI platform and LLM foundation provided by AI Platform & Foundation, delivers the AICL AI layer with D&T Data Engineering & Semantics and GCA DSM, and prepares the acceleration-to-scale handover with D&T Enterprise Engineering, Deployment & Operations and the Pfizer Innovation Center (PIC). It also engages relevant China Business Units and, where useful, International AIT engineering communities.

5. Measures of Success

• High-value ideas turned into working, evaluated prototypes and MVPs at speed.

• Technical feasibility, quality and safety proven through evaluation and guardrails before scale.

• Clean, well-documented handovers that accelerate production engineering by D&T and PIC.

• Reusable patterns, components and AICL AI-layer assets adopted across use cases.

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