Senior Director, Enterprise Architecture — Research & Development

About the role

Our IT organization delivers efficient, reusable technology solutions that accelerate business outcomes. Within Global Technology, the Enterprise Architecture team serves as a critical strategic partner — connecting technology investments to measurable business results. As AI rapidly reshapes pharmaceutical R&D — from molecule discovery and clinical trial design to regulatory intelligence and real-world evidence — we need strategic technology leadership more than ever.

We are seeking a Senior Director to lead Enterprise Architecture engagement for R&D, serving as a trusted enterprise technology advisor to R&D leadership and a strategic partner to business-facing IT partners across the division. This is not a traditional architecture role. It is a senior leadership position for someone who deeply understands the science, operations, and business of pharmaceutical R&D, and who can connect divisional outcomes to enterprise capabilities, platforms, standards, and technology direction.

The right candidate will help R&D leaders understand how enterprise technology investments — including AI and advanced analytics — can accelerate their pipeline, compress timelines, improve decision quality, and unlock new capabilities, while ensuring those investments are grounded in enterprise strategy, responsible AI principles, and measurable outcomes.

Organizational Context: This role is part of the Enterprise Architecture organization within Global Technology and leads Enterprise Architecture engagement for R&D. It operates as a trusted enterprise technology advisor to the Architecture Leadership Team and R&D senior leadership, and as a complementary strategic partner to business-facing IT partners. The role connects R&D priorities, outcomes, and capability needs to enterprise capabilities, platforms, standards, investments, and technology direction. It also represents R&D demand and strategic context within Enterprise Architecture so that enterprise decisions and capabilities better support divisional outcomes. The role advises, guides, and aligns where enterprise or cross-divisional implications exist, partnering with divisional architecture, product, domain, and delivery leaders who drive realization within R&D.

Key Responsibilities

Trusted Enterprise Advisor to R&D Leadership

• Develop trusted relationships with R&D senior leadership and the Architecture Leadership Team, providing an enterprise technology perspective that connects divisional priorities to enterprise capabilities, platforms, standards, investments, and future technology direction.
• Advise R&D leaders on enterprise technology opportunities, dependencies, risks, tradeoffs, and cross-divisional implications that may influence divisional outcomes.
• Help R&D leaders understand how enterprise capabilities, shared platforms, and technology investments can accelerate business objectives while reducing duplication, risk, and long-term complexity.
• Bring visibility to enterprise implications and cross-divisional dependencies early enough to inform planning and investment discussions before choices are locked.
• Represent R&D priorities, demand signals, and capability needs in enterprise technology and architecture discussions so they shape enterprise strategy, platforms, and investments.

Accelerate Business Outcomes

• Engage R&D leadership early to understand material outcomes, future demand, and enterprise implications across capability areas (discovery, lab operations, preclinical, clinical development, regulatory, pharmacovigilance, clinical supplies manufacturing).
• Connect divisional needs to enterprise capabilities, platforms, data, and shared dependencies — helping resolve enterprise barriers that could delay R&D outcomes.
• Drive AI acceleration across R&D: identify high-value use cases, prioritize AI investments by business impact, and ensure strategic alignment over fragmentation.
• Evaluate emerging technologies and industry trends (AI/ML, generative AI, Cloud, SaaS, advanced analytics, modern data integration) and translate them into actionable enterprise strategies that serve R&D.
• Bring a total-cost-of-ownership and business-outcomes lens to investment decisions, ensuring choices are evidence-based, priority-aligned, and sustainable at scale.

Make Technology Decisions Fast, Transparent, and Durable

• Own the quality and traceability of enterprise architecture decisions affecting R&D — ensuring decisions, rationale, dependencies, implications, and outcomes are visible and reusable.
• Clarify which decisions require enterprise alignment and which require senior governance, providing constructive guidance rooted in business context.
• Translate recurring enterprise decisions into standards, patterns, reference architectures, and self-service guidance — including responsible AI guardrails.
• Drive connected, trusted enterprise architecture data that improves planning, decision intelligence, reuse, optimization, and self-service access to architecture knowledge.

Optimize Through Reuse, Standardization, and Simplification

• Create visibility into cross-divisional reuse, platform leverage, duplication, lifecycle risk, and technical debt opportunities relevant to R&D.
• Quantify enterprise value and implications in partnership with portfolio, finance, product, and architecture leaders.
• Help convert agreed opportunities into roadmaps with clear owners — measuring opportunity visibility, reuse, complexity reduction, and realized enterprise value.
• Identify opportunities for shared platforms across divisions (manufacturing quality, animal health, and other business units) and champion value-centric technology decisions prioritized by business outcomes.

Shape and Realize the Future of Technology

• Bring R&D future demand and market signals into enterprise technology foresight — shaping enterprise capability and platform direction where R&D needs have broader relevance.
• Maintain an active network of peer organizations, analysts, suppliers, and leading-edge sources in pharma/life sciences technology — with particular attention to the evolving AI ecosystem.
• Advise R&D leaders on the implications and opportunities created by enterprise technology direction, connecting enterprise roadmaps to practical adoption paths.
• Translate external insights into practical recommendations that keep R&D technology strategy ahead of the curve.

Enterprise Architecture Leadership and Capability Building

• Lead Enterprise Architecture engagement for R&D, establishing clear priorities, accountability, and measurable outcomes aligned to the enterprise EA strategy.
• Develop and coach Enterprise Architecture talent supporting R&D, strengthening business acumen, strategic thinking, enterprise alignment, decision leadership, and domain depth.
• Represent R&D within Enterprise Architecture leadership forums and represent Enterprise Architecture perspectives within R&D leadership forums.
• Act as a senior delegate for Enterprise Architecture leadership in R&D-related planning, strategy, and governance discussions when required.
• Build succession depth for enterprise architecture leadership.

Required Skills

Deep R&D Domain Knowledge

• Thorough understanding of the end-to-end pharmaceutical R&D value stream — discovery through post-market evidence generation.
• Working knowledge of relevant regulations (21 CFR Part 11, GxP, CSV) and emerging regulatory expectations around AI in life sciences.
• Familiarity with laboratory instrumentation, scientific computing, clinical data platforms, and R&D operational systems at a strategic level.

AI & Advanced Analytics Acumen

• Strong understanding of how AI/ML and generative AI are being applied across pharma R&D — with a clear-eyed view of where they deliver real value versus where they remain aspirational.
• Ability to bridge data scientists, business leaders, and technology teams, ensuring AI initiatives are framed around business problems and measured by business outcomes.
• Commitment to responsible AI practices: fairness, transparency, and regulatory compliance.

Strategic & Enterprise Thinking

• Proven ability to develop technology strategies that bridge business vision and execution, with a track record of driving adoption and measurable results.
• Enterprise-level thinking: connecting divisional needs to organizational strategy, identifying cross-functional synergies, and optimizing for the whole.
• Experience navigating complex, matrixed organizations and influencing without direct authority. Comfortable in ambiguity.

Stakeholder Leadership & Communication

• Outstanding communication skills — able to distill complex technology concepts into compelling narratives for executive, business, and technical audiences.
• Skilled in evidence-based decision-making through structured analysis and persuasive storytelling.
• Demonstrated ability to build trusted advisory relationships with senior leaders through business acumen, follow-through, and sound judgment.

Modern Technology Fluency

• Strong grasp of Cloud, SaaS, AI/ML, data platforms, and modern integration patterns in pharmaceutical R&D contexts.
• Ability to evaluate vendor platforms and emerging technologies with a critical, business-first lens — assessing fit, risk, scalability, and TCO.

Qualifications

• Bachelor’s degree in Computer Science, Engineering, Information Security, or a related field.
• 15+ years in technology strategy, enterprise architecture, digital transformation, or related leadership roles — ideally with significant pharmaceutical, biotech, or life sciences R&D exposure.
• Self-directed leader who independently identifies needs, fills strategic gaps, and drives results with minimal direction.
• Demonstrated ability to lead teams, develop talent, and build succession depth in architecture or technology strategy functions.
• Effectively leverages diversity of thought and perspective to strengthen strategies and outcomes.
• Bachelor's or Master's degree in Information Science, Computer Science, Bioinformatics, Life Sciences, or a related field.