Head, AI Delivery & Enablement (aide), Director

Pfizer Pfizer · Pharma · MA

This role leads the strategy and technical direction for applied AI in Inflammation & Immunology at Pfizer, focusing on translating advances in LLMs, agentic systems, and multimodal AI into reusable capabilities. The position involves shaping the AI portfolio, defining governance and evaluation standards, managing external partnerships, and driving AI adoption across scientific decision-making processes. It requires a technically credible leader with strong scientific judgment to ensure solutions are robust, trusted, and improve the speed and quality of evidence generation.

What you'd actually do

  1. Set the strategic direction for AI Delivery & Enablement (AIDE) and define a clear roadmap for how large language models, agentic systems, multimodal AI, and related methods will be applied to high-value scientific problems across Inflammation & Immunology (I&I).
  2. Lead the AIDE portfolio across I&I, identifying, prioritizing, and shaping opportunities so that AIDE focuses on areas where technically credible, reusable AI capabilities can create meaningful scientific or operational leverage.
  3. Provide senior technical and scientific direction across the AIDE line, ensuring that proposed solutions are methodologically sound, fit for purpose, and grounded in biological, translational, and drug discovery context.
  4. Guide the development of reusable AI-enabled capabilities that strengthen scientific decision-making end-to-end, with emphasis on scientific rigor, technical quality, reproducibility, and practical utility across I&I lines.
  5. Establish governance and evaluation standards for AIDE-built capabilities, including expectations for provenance, validation, guardrails, responsible use, and appropriate human oversight.

Skills

Required

  • Advanced degree in computer science, machine learning, artificial intelligence, computational biology, bioinformatics, statistics, engineering, life sciences, or a related quantitative or scientific field
  • Demonstrated experience leading complex, cross-functional initiatives in applied AI, computational science, data science, digital transformation, or related domains
  • Strong hands-on understanding of LLMs, generative AI, machine learning, and related AI approaches
  • Demonstrated ability to identify, prioritize, and shape high-value use cases in ambiguous environments
  • Experience building and scaling reusable workflows, methods, products, or platforms
  • Demonstrated ability to develop strategy, shape AI portfolios, and communicate impact and return on investment to senior stakeholders
  • Strong matrix leadership, communication, and influence skills
  • Sound judgment regarding methodological rigor, evaluation, provenance, model limitations, risk, and the appropriate role of human oversight

Nice to have

  • Experience in life sciences, pharma, biotech, systems biology, immunology, translational science, omics, or related research environments
  • Demonstrated ability to operate fluently across AI / technology and biology

What the JD emphasized

  • reusable capabilities
  • scientific decision-making
  • governance and evaluation standards
  • reusable AI-enabled capabilities
  • reusable workflows, methods, products, or platforms

Other signals

  • leading strategy and technical direction for applied AI
  • translating advances into reusable capabilities
  • shaping the AIDE portfolio
  • defining governance and evaluation standards
  • accelerating practical AI adoption