This is a leadership role that builds and grows a dedicated agentic AI team, establishes the DDCS/PRD wide capability platform, and integrates it seamlessly into all processes of CMC development. As the functional technical leader, you partner with scientists, engineers and senior leaders across DDCS/PRD, Manufacturing, Discovery, Business Units, and corporate AI leadership to turn this vision into production reality. You’ll serve as a CMC champion for agentic AI in development sciences, setting direction, building durable platform assets, and proving measurable gains in speed, quality and productivity across the CMC development lifecycle.
1. Set the Agentic AI Strategy and Roadmap
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Serve as the single point of accountability for DDCS and pan PRD agentic AI strategy, setting a multi-year vision, roadmap and technology strategy for autonomous development systems.
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Define the future-state operating model for an AI-enabled development organization and prioritize the highest-value opportunities for transformation.
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Build the business case and champion narrative that win support from scientists, engineers and senior leaders, addressing both the opportunity and the risks of agentic AI openly and directly.
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Track Lilly’s growing portfolio of agentic AI initiatives and external pharma agentic AI moves, translating industry and competitive trends into roadmap decisions.
2. Own the Agentic AI Platform Architecture
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Lead development of an enterprise-scale platform spanning multi-agent orchestration frameworks, large language model ecosystems, agent memory architectures, retrieval-augmented generation and knowledge graph systems, digital twin and simulation integration, and autonomous workflow engines.
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Establish standards for agent-to-agent and tool communication (for example, Model Context Protocol and Agent-to-Agent standards) so agents work together across the pan PRD data and knowledge landscape.
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Build reusable enterprise capabilities that DDCS, BRD, SMDD and Manufacturing can all adopt.
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Build in responsible AI controls from the start: human-in-the-loop quality systems, AI governance and compliance frameworks, and GxP/21 CFR Part 11 auditability for every agent output that touches a regulatory submission.
3. Build and Lead the Agentic AI Development Team
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Recruit, build and lead a world-class team of AI scientists, AI application engineers, software architects, product managers, workflow transformation leaders and domain experts.
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Recruit and develop top talent from the pharmaceutical, technology, AI and startup ecosystems, building an organization recognized as an industry leader in applying agentic AI to scientific and engineering development.
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Foster a culture of experimentation, innovation, speed and continuous learning.
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Talent Magnet and Builder: Attract, develop and retain exceptional technical and business talent while building future leadership pipelines.
4. Lead Agentic Solution Development End-to-End
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Lead deployment of intelligent agent ecosystems across CMC development workflows, including scientific knowledge discovery and synthesis, literature mining and competitive intelligence, experiment planning and optimization, formulation design support, process development optimization, design, technical report authoring, regulatory submission content generation, and quality investigations.
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Develop full-stack applications that integrate large language models, retrieval-augmented generation and agentic workflows with intuitive front ends and secure back-end services, automating today’s manual CMC development data and documentation tasks.
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Drive the transition from manual, document-centric workflows to autonomous, AI-native development processes, monitoring and evaluation practices that keep agents accurate, fast and cost-effective after launch.
5. Orchestrate Cross-Functional Delivery with CMC development partners
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Serve as the bridge between DDCS/PRD scientists, engineers, quality, manufacturing and regulatory colleagues and the technical team, translating business needs into technical requirements and technical capability into business value.
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Partner with corporate AI, digital and business leadership to align DDCS and PRD initiatives with Lilly’s broader AI strategy, driving adoption of agentic operating models, enterprise copilots and next-generation digital worker concepts.
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Coordinate with Tech@Lilly and Enterprise IT so agentic AI work stays aligned with enterprise platforms and standards rather than running as a parallel effort.
6. Own the Business Case, ROI and Success Metrics
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Define and track efficiency, cycle-time, quality and adoption metrics that show agentic AI’s impact on CMC development speed and output.
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Own the ROI narrative for agentic AI investment in DDCS/PRD, reporting measurable reductions in development cycle time and technical workload to senior leadership.
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Build durable, reusable automation assets, not one-off pilots, so gains compound across programs and years.
7. Drive Adoption and Change Management
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Lead change management for new agentic AI capabilities: stakeholder engagement, communications, training and deployment support so agents get embedded in real workflows, not just piloted.
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Establish feedback loops with scientists and engineers to identify adoption barriers, prioritize enhancements and build a culture of responsible AI adoption across DDCS.
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Free scientist and engineer time from repetitive, document-heavy work so they can focus on the creativity- and judgment-based work that drives real innovation.
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Represent Lilly’s agentic AI-for-CMC agenda in industry consortia, regulatory forums and academic partnerships, and build strategic relationships with leading AI companies and technology providers that bring outside perspective into DDCS.
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Organizational Transformation: Lead transformational change across complex, matrixed organizations while delivering measurable business outcomes.
8. Scientific leadership in Lilly and pharma industry
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Create breakthrough strategies that redefine how development work is performed and position Lilly for sustained competitive advantage, building Lilly’s reputation as a leader in agentic AI-enabled drug delivery and development.
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Advance disruptive technologies and operating models that meaningfully improve portfolio performance and enterprise productivity.
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Influence Beyond Authority: Align diverse stakeholders across organizations, geographies and disciplines toward a common vision. Build and use a diverse external network across industry, academia and regulatory bodies to bring outside perspective and speed breakthrough thinking inside DDCS.
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External Impact: Shape industry practices, build strategic partnerships, and establish Lilly as a recognized leader in agentic AI-enabled pharmaceutical development.