At Lilly, the work is demanding because patients are waiting. We unite caring with discovery to help make life better for people around the world, knowing that every decision, every detail, and every day matters. Headquartered in Indianapolis, Indiana, our over 50,000 employees around the globe take on complex challenges to discover and deliver life-changing medicines, strengthen how health is understood and managed, and support the communities we serve. This is hard, urgent, selfless work—but it’s work worth doing. If you’re driven by purpose and ready to bring your best to work that truly matters for patients, we invite you to join us.
LRL takes potential marketable products from Research through product registration and approval, enabling MDU's business needs of the future through information and technology solutions. Within this portfolio, Clinical Supply & Delivery (CS&D) owns the systems and platforms that move investigational drug product — from packaging and labeling through distribution and fulfillment — to clinical trial sites, reliably, compliantly, and on time for trial execution. The CS&D Technical Lead Architect owns end-to-end technical architecture for these platforms — moving CS&D from point-solution delivery to a coherent, agentic-AI-enabled architecture, and from reactive engineering support to proactive, roadmapped portfolio transformation.
Path/Level: R5 (CS&D Technical Lead Architect)
This role is split roughly 70% hands-on technical execution — building agentic architecture, integration patterns, and platform capability directly — and 30% strategy, roadmap ownership, and portfolio-level transformation planning. The CS&D Technical Lead Architect shapes the future technology landscape for CS&D's clinical supply and trial-material delivery platforms, aligning business strategy with technology investment, AI/agentic innovation, and architecture to drive operational excellence, compliance, and scalable transformation.
Key Responsibilities
- Portfolio Architecture Ownership (Hands-On) — design, build, and directly implement the technical architecture for CS&D's critical platforms — containerized services, CI/CD pipelines, cloud infrastructure, data pipelines, and integration layers; own architecture roadmaps and standards for the platforms in scope, preparing decisions ahead of delivery rather than resolving them reactively. (placeholder — confirm scope: demand/supply forecasting, packaging & labeling, distribution and site-level fulfillment, trial-material tracking)
- Agentic AI & Portfolio Transformation — drive a portfolio-wide exploration of AI/agentic opportunities across CS&D's platforms; evaluate build-vs-buy for each opportunity; own and evolve a staged, roadmapped vision for shifting CS&D's architecture toward agentic-based patterns wherever viable, sequencing the transformation gradually rather than as a single cutover; convert validated proofs-of-concept into production-grade, reusable agentic architecture.
- Governance, Risk & GxP/GCP Compliance — embed audit-readiness, security and change-control thinking into architecture patterns; ensure designs meet FDA/EMA and internal IT/quality policy requirements, including GMP, GCP considerations relevant to clinical trial material handling; maintain architecture documentation supporting audit, inspection, and CSV readiness across the platforms owned.
- Technology Evaluation & Platform Modernization — evaluate emerging cloud, data, and AI/agentic technologies for CS&D applicability; run staged proofs-of-concept before adoption; identify and retire technical debt, consolidating and simplifying the platform footprint.
- Business & Product Partnership — partner with product managers and business stakeholders to translate business goals, capabilities, and value-streams into technical solutions; lead architectural discussions and decision-making, facilitate knowledge-sharing, and manage expectations through clear communication.
- Decision-Making (Platform-Scoped) — hold design and integration decision authority within the CS&D platforms owned end-to-end; approve implementation-level architecture and integration patterns; escalate — rather than unilaterally resolve — enterprise-architecture, investment-level, or cross-portfolio GxP risks that sit outside platform scope.
- India-Led Global Ownership — represent CS&D Tech in relevant architecture forums; build shared ownership and accountability between the India team and global stakeholders; grow India as the technical decision-making center for the platforms owned, not just a delivery location.
- Talent Development & Technical Leadership — conduct code reviews and provide hands-on guidance to development teams; mentor engineers toward stronger architecture and agentic-design capability; contribute to hiring and technical talent planning.
Technical & Strategic Expertise Areas
Enterprise & Solution Architecture · Agentic AI & Multi-Agent Architecture · Generative AI · Architecture Design Patterns (N-tier, Microservices, Event-Driven/Reactive, Batch/Micro-Batch/Real-Time) · Containerization & Orchestration (Docker, Kubernetes) · CI/CD & DevOps (GitHub Actions, AWS CodePipeline/Copilot) · Cloud Platforms (AWS: EC2, S3, RDS, Lambda, Glue, Redshift/Redshift Spectrum, Athena) · Event-Driven Architecture (Kafka, RabbitMQ, SNS/SQS) · API & Integration Architecture · Data Architecture (RDBMS, NoSQL, Data Pipelines, Search Engines) · Spark/PySpark, Hadoop · Caching & CDN (Redis, CloudFront) · Front-End & Back-End Development (React, Node.js, Python, Django/Flask) · Cloud/Platform Migration · Security & Compliance Architecture (GxP, GCP, CSV) · Platform Engineering · Portfolio-Level Problem Breakdown
Basic Qualifications
- Bachelor's degree in Computer Science, Information Systems, Engineering, or related field (Master's preferred).
- 12+ years in solution/enterprise architecture or senior technical leadership, with direct, ongoing coding/build involvement — not oversight-only experience.
- Proven experience designing, building, and deploying agentic/AI architecture, including evaluating build-vs-buy for AI/agentic capability; experience implementing AI/ML tech stacks within production programs.
- Strong hands-on experience with containerization and orchestration (Docker, Kubernetes), CI/CD pipelines, and DevOps practices.
- Strong grasp of architecture design patterns — N-tier, microservices, stateful vs. stateless, request-response vs. loose-coupling vs. reactive, batch/micro-batch/real-time processing.
- Advanced proficiency in Python and JavaScript, with fullstack experience (React, Node.js).
- Solid experience with relational and NoSQL databases (PostgreSQL, MySQL, MongoDB, DynamoDB), search engines, and AWS ETL services (Glue, Data Pipeline, Redshift Spectrum).
- Experience with event-driven architecture (Kafka, RabbitMQ, AWS SNS/SQS).
- Ability to design, build, and unit test applications on the Spark framework in Python, including PySpark for batch and streaming workloads.
- Experience operating in regulated (GxP/GCP) environments, including computer system validation (CSV) and inspection-readiness practices.
- Experience with clinical trial data — its structure, sourcing, and use in supply chain / trial execution contexts.
- Track record translating business goals and value-streams into technical architecture decisions.
- Demonstrated ability to mentor engineers and lead architectural discussions without requiring a formal people-manager structure.
Additional Qualifications / Competencies
- Strategic and analytical thinking — sequencing a multi-year agentic transformation roadmap rather than one-off point solutions.
- Experience representing India-based technical teams in global architecture or governance forums.
- Comfort operating in ambiguity, driving clarity around architecture dependencies and transformation sequencing.
- Experience leading platform or data migration initiatives.
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