Head, AI Delivery & Enablement (AIDE), Director
Pfizer
6 hours ago
Remote friendly (Cambridge, MA)
United States
IT
ROLE RESPONSIBILITIES
- Set the strategic direction for AI Delivery & Enablement (AIDE) and define a clear roadmap for applying large language models, agentic systems, multimodal AI, and related methods to high-value scientific problems across Inflammation & Immunology (I&I).
- Lead the AIDE portfolio across I&I by identifying, prioritizing, and shaping opportunities to focus on areas where reusable AI capabilities create meaningful scientific or operational leverage.
- Provide senior technical and scientific direction across the AIDE line to ensure solutions are methodologically sound, fit for purpose, and grounded in biological, translational, and drug discovery context.
- Guide development of reusable AI-enabled capabilities that strengthen scientific decision-making end-to-end, emphasizing scientific rigor, technical quality, reproducibility, and practical utility.
- Establish governance and evaluation standards for AIDE-built capabilities, including provenance, validation, guardrails, responsible use, and appropriate human oversight.
- Partner with Systems Immunology, I&I line teams, and Digital partners to align AI efforts with real scientific needs and ensure trusted, scalable deployment and adoption.
- Shape and manage selected external partnerships by evaluating emerging technologies and collaborators aligned to AIDE priorities.
- Articulate the value and impact of the AIDE portfolio to senior stakeholders, including rationale, differentiation, adoption trajectory, and ROI.
- Build a strong technical culture within AIDE to foster collaboration, continuous learning, and confidence in responsible AI use.
BASIC QUALIFICATIONS
- BS + 8+ years OR MS + 7+ years OR PhD + 5+ years in a relevant field (CS/ML/AI, computational biology/bioinformatics, statistics, engineering, life sciences, or related quantitative/scientific area).
- Demonstrated experience leading complex, cross-functional initiatives in applied AI/computational science/data science/digital transformation, including strategy, portfolio prioritization, and value realization.
- Strong hands-on understanding of LLMs, generative AI, and machine learning; credibility to guide decisions, assess trade-offs, and challenge weak approaches.
- Ability to identify, prioritize, and shape high-value use cases in ambiguous environments and translate needs into reusable, measurable-impact solutions.
- Experience building and scaling reusable workflows/methods/products/platforms (not one-off analyses).
- Ability to develop strategy, shape AI portfolios, and communicate impact and ROI to senior stakeholders.
- Strong matrix leadership, communication, and influence skills to drive adoption without relying only on formal authority.
- Sound judgment on methodological rigor, evaluation, provenance, model limitations, risk, and appropriate human oversight in AI-enabled scientific workflows.
PREFERRED QUALIFICATIONS
- Experience in life sciences, pharma, biotech, systems biology, immunology, translational science, omics, or related research environments.
- Ability to operate fluently across AI/technology and biology, engaging credibly with scientists and line leaders.
APPLICATION INSTRUCTIONS
- Last date to apply: April 30, 2026.
- Set the strategic direction for AI Delivery & Enablement (AIDE) and define a clear roadmap for applying large language models, agentic systems, multimodal AI, and related methods to high-value scientific problems across Inflammation & Immunology (I&I).
- Lead the AIDE portfolio across I&I by identifying, prioritizing, and shaping opportunities to focus on areas where reusable AI capabilities create meaningful scientific or operational leverage.
- Provide senior technical and scientific direction across the AIDE line to ensure solutions are methodologically sound, fit for purpose, and grounded in biological, translational, and drug discovery context.
- Guide development of reusable AI-enabled capabilities that strengthen scientific decision-making end-to-end, emphasizing scientific rigor, technical quality, reproducibility, and practical utility.
- Establish governance and evaluation standards for AIDE-built capabilities, including provenance, validation, guardrails, responsible use, and appropriate human oversight.
- Partner with Systems Immunology, I&I line teams, and Digital partners to align AI efforts with real scientific needs and ensure trusted, scalable deployment and adoption.
- Shape and manage selected external partnerships by evaluating emerging technologies and collaborators aligned to AIDE priorities.
- Articulate the value and impact of the AIDE portfolio to senior stakeholders, including rationale, differentiation, adoption trajectory, and ROI.
- Build a strong technical culture within AIDE to foster collaboration, continuous learning, and confidence in responsible AI use.
BASIC QUALIFICATIONS
- BS + 8+ years OR MS + 7+ years OR PhD + 5+ years in a relevant field (CS/ML/AI, computational biology/bioinformatics, statistics, engineering, life sciences, or related quantitative/scientific area).
- Demonstrated experience leading complex, cross-functional initiatives in applied AI/computational science/data science/digital transformation, including strategy, portfolio prioritization, and value realization.
- Strong hands-on understanding of LLMs, generative AI, and machine learning; credibility to guide decisions, assess trade-offs, and challenge weak approaches.
- Ability to identify, prioritize, and shape high-value use cases in ambiguous environments and translate needs into reusable, measurable-impact solutions.
- Experience building and scaling reusable workflows/methods/products/platforms (not one-off analyses).
- Ability to develop strategy, shape AI portfolios, and communicate impact and ROI to senior stakeholders.
- Strong matrix leadership, communication, and influence skills to drive adoption without relying only on formal authority.
- Sound judgment on methodological rigor, evaluation, provenance, model limitations, risk, and appropriate human oversight in AI-enabled scientific workflows.
PREFERRED QUALIFICATIONS
- Experience in life sciences, pharma, biotech, systems biology, immunology, translational science, omics, or related research environments.
- Ability to operate fluently across AI/technology and biology, engaging credibly with scientists and line leaders.
APPLICATION INSTRUCTIONS
- Last date to apply: April 30, 2026.