For this Director-level role, we areseekinga scientific and technicalexpertto leadouragentic AIco-scientist initiativeacross our scientificorganization.This individual willserve as the scientific leadon the project,defining and influencingthe strategy,architecture,evaluation framework, and delivery plan for co-scientist capabilities across multiple scientific use cases and functions.This effort will spanboth internaldevelopment ofcapabilities and rigorous evaluation of externally available tools.As the senior scientificleaderof the effort,this individual willalign cross-functional stakeholders,prioritize scientificneeds and capabilities,anddrivemeasurable progress, adoption, and delivery of a trusted AI capability that augments scientific reasoning, hypothesis generation, experimental planning, and decision support.

This is a Boston based, hybrid position requiring 3 days/week onsite.

Key Duties & Responsibilities:

• Serve as the senior scientific leader for theagentic AIco-scientist project.Through matrixed leadership,leada cross-functional team across scientific, computational, and technical areas to definepriorities, translateVertex scientific needs into a sequenced roadmap, and deliver scalable agentic AIcapabilities.Ensurethe initiativeremainsaligned topriority scientificneedsacross projects, research sites,andmodalities, with clear goals, decision rights, dependencies, risks, and outcomes.
• Drive scientificandtechnical leadership for internal development of co-scientist capabilities, including development of scientific systemskills, integrating existing scientificdatasets and methods,anddefining agentic roles,skills, and orchestration patterns.
• Lead evaluation of internal and external agentic AI capabilities. Define evidence-based frameworks, benchmarks, and governance to assess commercial, partnership, open-source, and internally developed options and inform build, buy, partner, or integrate decisions.
• Establish rigorous scientific validation standardsand governanceframework.Define acceptance criteria and ongoing evaluation approaches forcorrectness, relevance, novelty, reliability, reproducibility, provenance, uncertainty, usability, andmeasurableimpact onscientificdecision-making.
• Drivedevelopment and deployment across scientific domains and modalities. Partner withscientificleadersand domain expertstoidentifyhigh-valueuse cases, translatescientific workflows into agentic AI opportunities, and guide delivery from prototypetosupported adoptionwhile preservinghuman scientific judgment and accountability.
• Representthe co-scientist effort with executive and senior leader stakeholders, providing clear communication on strategy, tradeoffs, progress, risks, resource needs, and delivery milestones, withappropriate decisionescalation as needed.
• Shape agentic AI workflows and scientific operating models. Definehow agents, models, tools, data, literature, compute, and expert reviewwork together to support complex research questionswithappropriateplanning, traceability,escalation,andreproducibility.
• Influence data, platform, and infrastructure strategy.Partner withinfrastructureand platform leaders to definefoundationalrequirements for trusteddataaccess, knowledge management, model and tool integration,scalable compute, and reliable expansionacross functions and modalities.
• Ensure delivery and adoption by driving milestone-based execution, use-case prioritization, change management, stakeholder alignment, and evidence-based decisions on where co-scientist capabilities produce meaningful scientific and organizational value.
• Drive innovationthroughtimelyknowledge ofemergingtechnologies, advancements, and challenges in thefield of scientificagentic AI,andleveragethese external insights todrive a best-in-class AI co-scientisttool

Knowledge and Skills:

• Deepunderstanding ofdrugdiscoveryand scientific researchworkflows andhowshared AI capabilitiescan addressdomain-specific needs across functions, therapeutic areas, and modalities.
• Deepexpertisein modern AI, including LLMs, agentic systems, scientific foundation models, retrieval, tool use, planning, and evaluation.
• Abilityto define rigorous evaluations, benchmarks, validation strategies, and success measures for AI-enabledscientifictools and workflows.
• Exceptional ability to partner effectively withinfrastructure and platform collaborators, throughplatform architecture, tool integration, scalablecompute, and reproducible workflows.
• Exceptional ability to partner effectively with scientific collaborators, through stronggrasp of scientificneedsin drug discovery and research, scientificdata strategy,andstrategic understanding of relative prioritization and impact of different opportunities.
• Strong strategic judgment, executive communication, stakeholder management, collaboration, and mentoring skills.
• Excellent presentation, verbal, and written communication skills, including effective communication with senior leaders and cross-functional stakeholders
• Commitment to scientific rigor, responsible AI, reproducibility, transparency, data governance, cybersecurity, privacy, andappropriate humanoversight.
• Demonstrated ability and willingness to teach,engageand support others as they learnnew technologiesand concepts
• Enthusiasm for and the ability to quickly learnnew technologiesand tackle difficult problems

Educationand Experience

• Ph.D. in Computer Science, Artificial Intelligence, Machine Learning, Computational Biology, Computational Chemistry, Bioinformatics, Engineering, Applied Mathematics,with10+ years of relevantexperiencein scientific drug discovery and research, or comparable training and experience.
• Seniorscientific and technical leadershipexperiencein drug discovery, life sciences, AI/ML, computational science,or a closely relatedfield.
• Track recordleading complex, cross-functional initiatives from strategy through delivery, adoption, and measurable impact.
• Experiencedeveloping, evaluating, deploying, or governing advanced AI, machine learning, computational, or data-driven systems ina scientifically rigorous environment.
• Demonstratedability to influence senior stakeholders, alignteamswithout direct authority, andmakedecisions amid scientific,technical, and organizationalambiguity.
• Experience assessing external technologiesorpartnerships andrecommendingbuild, buy, partner, adapt, orintegrateoptionsbased on evidence and strategic value.
• Recognizedscientific impactthroughpublications, patents, deployed capabilities,external presentations,or comparable contributions.

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