Associate Director — PR&D Delivery & Operations

Overview

Lead broader delivery teams across CMC data platform modernization, scientific workflow automation (LIMS, MES, ELN), data governance and business alignment, and AI & Analytics delivery, accountable for delivery, technical direction, team capability and measurable business outcomes. Split roughly 60% delivery and technical leadership and 40% strategy, business partnership and vendor leadership.

What you'll do

• Own delivery across the portfolio: scope, schedule, quality, dependencies, release readiness and production health for CMC data and semantic infrastructure, platform modernization and operations, and AI-use-case delivery, directing the broader teams accountable for each track.
• Run delivery on real signals: flow, predictability, defect escape and adoption by scientific and process teams, not status reporting.
• Set and defend the technical direction of the portfolio, contributing to how CMC data platforms support the goals of the wider PR&D business area.
• Review architecture and design, challenge weak decisions, and own standards for APIs, data contracts, ontology and knowledge-graph modeling (RDF/OWL/SPARQL, property graphs), and tool-calling interfaces (MCP) across CMC data platforms.
• Raise the engineering bar on test automation, CI/CD, observability and the deliberate reduction of technical debt.
• Support delivery of AI and agentic use cases already on the portfolio roadmap, including document and schema intelligence, retrieval over CMC content, and knowledge-graph-powered Q&A or summarization agents, with the same delivery rigor, resourcing and release discipline as other workstreams.
• Help bring new AI use cases forward for evaluation, and support them through validation and into production with appropriate guardrails and human-in-the-loop review.
• Act as the technology partner for PR&D business owners and domain product managers across the portfolio's data, platform and AI-use-case tracks.
• Capture and challenge incoming demand, agree priorities against capacity, and keep one honest view of the roadmap and what has been traded away.
• Translate CMC and scientific need into technical options, and constraint, risk and cost into language a business owner can act on; set a rhythm of business reviews and early warning.
• Build the case for modernization investment, with the benefit measurement that follows it.
• Define scope, outcomes and acceptance criteria for partner teams, and hold suppliers to the same engineering, quality and GxP standards as internal teams.
• Shape the sourcing mix for the portfolio, plan partner ramp-up and ramp-down against the roadmap, and manage supplier performance on predictability, quality and knowledge retention.
• Work with sourcing, legal and finance on statements of work, capacity models and change requests.
• Integrate partner engineers into one team, one backlog and one set of standards, and protect institutional knowledge through documentation, code ownership and cross-training.
• Deliver in a GxP-regulated environment, including computer system validation, 21 CFR Part 11, data integrity, inspection and audit readiness.
• Design for security and data privacy from the start, meet architecture and security review obligations early, and own incident response and service levels for the products the teams run.
• Manage, coach and grow broader delivery teams spanning multiple sub-teams and disciplines, including clear expectations, specific feedback, honest check-ins and development plans.
• Hire for the capability the portfolio needs next, address underperformance without delay, build bench strength and succession, and remove single points of failure.
• Make design, tooling, sequencing and sourcing decisions within the guidelines set by architecture, engineering and validation standards; forecast resource needs and manage the allocated budget against plan.
• Escalate policy-level or cross-platform decisions with a recommendation rather than a question.

What you'll need

• Bachelor's degree in Computer Science, Information Systems, Engineering or a related field.
• 10+ years in technology delivery or technical leadership, including 4+ years of direct people management across broader or multi-team delivery organizations.
• 4+ years supporting CMC, pharma R&D, or manufacturing data and process technology, including LIMS/MES/DMS/ELN systems, batch records, process or regulatory submission data.
• Demonstrated ownership of delivery for a portfolio or platform across multiple concurrent programmes, including work delivered through vendors.
• Broad technology awareness and working strength across cloud platforms, APIs and enterprise integration patterns, data engineering, AI/ML, and agentic systems, enough to review a design, engage credibly with technical teams, and spot delivery or quality risk, without requiring hands-on ownership of any single one.
• Working familiarity with AI, machine learning or agentic solutions and how they move from proof of concept into governed production use.
• Experience operating in regulated (GxP) environments, including computer system validation and inspection-readiness practices.
• Demonstrated success owning a senior business relationship, shaping demand, negotiating priorities and capacity, and holding credibility through difficult delivery news.
• Demonstrated success governing multi-vendor or managed-service delivery, with clear separation of Lilly-owned and vendor-executed responsibility, and command of the commercial mechanics.
• Strong communication skills, translating technical trade-offs into business, scientific and regulatory language for senior stakeholders.
• Working knowledge of Agile-at-scale and product operating model practices (backlog governance, value-stream mapping) applied to a regulated portfolio.
• Track record of hiring, coaching, performance management and retention across broader, distributed delivery teams.

Nice to have

• Master's degree.
• Experience with knowledge graph or ontology engineering platforms (Neo4j, GraphDB, Protégé, or comparable), or semantic layer/retrieval tooling; platform training or certification.
• Exposure to CMC, manufacturing, or process data domains, including batch records, equipment/material master data, or regulatory submission content.
• Strategic and analytical thinking, preparing decisions ahead of delivery rather than reacting to them.
• Strong vendor governance and negotiation skills; ownership mindset managing multiple priorities, stakeholders and concurrent programmes.
• Influence with internal and external customers and management, including business stakeholders who do not report to them and partner teams they do not employ.
• Learning agility and continuous-improvement leadership.
• Experience of shared ownership models between India-based and global organisations.

Details

• Location: Lilly Bengaluru, India.
• Split of roughly 60% delivery and technical leadership and 40% strategy, business partnership and vendor leadership.