Director, GBS, Forward Deployed Engineer

Role Summary

The Forward Deployed Engineer (FDE) is a hands-on technologist and trusted innovation partner to Global Business Services (GBS), embedded at the intersection of global business processes, transactional data and enterprise technology. Operating within Pfizer Digital & Technology’s Enabling Functions Forward Impact Engineering team, this role translates bold ideas into working AI and data-driven prototypes that accelerate the way we discover, develop, and deliver innovative solutions. FDEs work in small, mission-focused Pods aligned to specific EF domains such as Finance, GBS, PX and Legal/Compliance, co-owning a domain’s innovation backlog—from idea intake through proof-of-concept delivery and transition to enterprise scale. The ideal candidate combines engineering depth, creative problem solving, and business fluency, thinking like an AI architect, building like a full-stack engineer, and acting as a strategic partner driving measurable impact through technology that advances science.

Responsibilities

• Prototype & Deliver Innovation
  • Rapidly design and build AI- and data-driven prototypes addressing high-value GBS use cases (e.g., predictive modeling, scientific data integration, knowledge assistants, document intelligence, or lab automation).
  • Collaborate with enterprise data, platform, and engineering teams to ensure scalability and secure handoff of validated solutions.
  • Apply best practices in software development, data science, and MLOps to deliver maintainable, well-documented prototypes.
• Partner with GBS Leadership
  • Serve as the primary AI and technology thought partner for senior GBS leaders (VP/SVP level).
  • Translate scientific and operational pain points into technical opportunities with clear business value.
  • Influence decision-makers through demonstrations, storytelling, and measurable outcomes.
• Shape the Innovation Backlog
  • Work with Product Managers to source, assess, and prioritize ideas in the GBS Innovation Backlog.
  • Conduct feasibility assessments and align solutions to enterprise architecture, data governance, and AI safety standards.
  • Help define success metrics, business cases, and transition plans for scaled adoption.
• Enable Collaboration Across Digital & Technology & GBS
  • Build bridges between research scientists, enterprise Digital & Technology, data engineering, and AI platform teams.
  • Share learnings and reusable assets across Pods to accelerate innovation velocity.
  • Mentor emerging technical talent and help establish the culture of AI in service of science.

Qualifications

• Required: Bachelor's degree and 8+ years of experience in software engineering, data science, or applied AI, including 3+ years in a lead technical or product innovation role; or Master’s Degree and 7+ years of experience; or PhD with 5+ years of experience.
• Required: Proven ability to build working prototypes and AI applications using modern languages and frameworks (e.g., Python, PyTorch, TensorFlow, LangChain, FastAPI).
• Required: Deep understanding of data platforms, APIs, and cloud ecosystems (AWS, Azure, GCP).
• Required: Strong grasp of machine learning and generative AI concepts, including LLMs, NLP, and multimodal systems.
• Required: Excellent communication and storytelling skills; capable of translating complex ideas to non-technical audiences.
• Required: Demonstrated success influencing senior stakeholders and driving alignment in a matrixed, global organization.
• Preferred: Experience in pharma or corporate finance computing environments.
• Preferred: Familiarity with regulated domains (e.g., GxP, SOX).
• Preferred: Track record of leading cross-functional innovation initiatives from ideation to adoption.
• Preferred: Contributions to open-source projects, technical publications, or patents in AI/ML.

Skills

• AI/ML concepts including large language models, NLP, and multimodal systems
• Prototyping and rapid experimentation
• Storytelling and executive communication
• Stakeholder management and cross-functional collaboration
• Enterprise data governance, data integration, and AI safety standards

Education

• Bachelor’s degree in a relevant field with 8+ years of experience, or Master’s degree with 7+ years, or PhD with 5+ years in software engineering, data science, or applied AI

Additional Requirements

• Travel up to 25% may be required for business activities.
• Work Location: Hybrid