Senior Data & AI Solutions Architect

Eli Lilly and Company • Us, IN

18h • Onsite

About The Position

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. Senior Data & AI Solutions Architect Lilly’s Purpose At Lilly, we unite caring with discovery to make life better for people around the world. We are a global healthcare leader headquartered in Indianapolis, Indiana. Our employees around the world work to discover and bring life-changing medicines to those who need them, improve the understanding and management of disease, and give back to our communities through philanthropy and volunteerism. We give our best effort to our work, and we put people first. We are looking for people who are determined to make life better for people around the world. Come help us transform Lilly’s Manufacturing and Quality business! The Global Data, Analytics and AI team for Manufacturing and Quality is focused on delivering accelerated business value through Durable Analytic Products, Data as a Product, Data Products, and AI Products. We are looking for a hands-on technical leader who can architect and deliver Data, Analytics, and AI products for Manufacturing & Quality and who brings experience working with Quality Assurance processes in a regulated environment. As Lilly advances its Quality transformation journey, this role will shape and deliver solutions supporting Quality Assurance, Quality Management Systems, inspection readiness, quality risk management, deviation management, CAPA, complaints, audits, and broader Quality operations. The successful candidate will combine strong technical depth with product leadership and Quality domain knowledge. This individual will be expected to make architecture decisions, guide engineering teams, contribute directly to solution design and prototyping, and lead products from concept through production deployment and adoption.

Requirements

• Bachelor’s degree in Computer Science, Engineering, Data Science, Information Systems, or a related technical or scientific discipline.
• 12+ years of relevant experience in solution architecture, data architecture, data engineering, analytics engineering, AI/ML, software engineering, and/or digital product delivery.
• Experience designing and delivering enterprise-scale Data, Analytics, or AI products.
• Experience working with Quality Assurance processes in a pharmaceutical, biotechnology, manufacturing, healthcare, or another regulated environment.
• Experience leading technical teams or product pods through architecture, development, testing, deployment, and production support.
• Strong communication, problem-solving, technical leadership, and stakeholder-management skills.
• Data architecture, data engineering, data integration, data modeling, and modern analytics architecture.
• Cloud platforms such as AWS and/or Azure.
• Technologies such as Databricks, Spark, Redshift, Snowflake, Athena, Postgres, or comparable platforms.
• Scalable data pipelines, curated data layers, semantic models, APIs, analytical applications, and reusable data products.
• Relational, non-relational, and analytical data stores.
• SQL and analysis of complex enterprise data domains.
• Data governance, metadata, lineage, master data, and data-quality practices.
• Git-based source control, CI/CD, automated testing, DevOps, and production observability.
• Secure architecture, role-based access, privacy, monitoring, logging, and operational support.
• Demonstrated ability to translate business requirements into scalable technical solutions.
• Hands-on or technical leadership experience delivering AI/ML solutions.
• Experience with Generative AI, large language models, prompt engineering, RAG, vector stores, embeddings, semantic search, knowledge graphs, or AI orchestration frameworks.
• Experience with AI/ML frameworks such as TensorFlow, PyTorch, scikit-learn, LangChain, Semantic Kernel, or comparable technologies.
• Experience designing AI solutions with human-in-the-loop controls, explainability, evaluation, monitoring, and governance.
• Understanding of model lifecycle management, AI risk, and Responsible AI practices.
• Ability to distinguish among automation, analytics, decision support, and autonomous workflow opportunities.
• Experience working within Quality Assurance organizations or other regulated business functions.
• Knowledge of GxP, Quality Management Systems, deviations, CAPA, complaints, change control, audits, inspection readiness, Quality Risk Management, laboratory operations, or batch release.
• Experience delivering technical or AI-enabled solutions within regulated environments.
• Understanding of data integrity, validation, Software Assurance, cybersecurity reviews, electronic records, and AI governance.
• Operates as a technical leader who can move effectively among strategy, architecture, prototyping, and implementation.
• Remains hands-on enough to evaluate designs, challenge technical assumptions, and guide engineering teams.
• Uses business outcomes and intended use to drive architecture decisions.
• Makes clear, evidence-based technical recommendations.
• Demonstrates learning agility, intellectual curiosity, and interest in emerging technologies.
• Builds effective relationships across business, Quality, engineering, architecture, and governance teams.
• Develops others through technical mentoring, coaching, and constructive design feedback.

Nice To Haves

• Knowledge of GxP, Pharmaceutical manufacturing processes and automations systems.

Responsibilities

• Define, design, build, and scale data and AI solution architecture for Global Manufacturing and Quality teams.
• Lead product-based delivery pods across Data Products, Durable Analytic Products, Advanced Analytics, AI Products, and Agentic AI capabilities.
• Serve as a senior technical leader and solution architect for transformation programs, helping the organization move from fragmented reporting and manual analysis toward scalable, reusable, governed, and intelligent digital capabilities.
• Remain close to the technology, provide technical direction to engineers and data scientists, challenge solution designs, contribute to prototypes and technical problem-solving, and ensure products are engineered for secure, scalable, and sustainable production use.
• Define end-to-end architectures for Data Products, Durable Analytic Products, analytics applications, AI Products, and Agentic AI solutions.
• Architect solutions across data ingestion, transformation, orchestration, storage, semantic modeling, analytics, visualization, AI, integration, and application layers.
• Translate Manufacturing and Quality business requirements into practical technical designs, implementation patterns, and product roadmaps.
• Provide hands-on leadership in solution design, data modeling, architecture blueprints, technical spikes, and prototype development.
• Design scalable data pipelines, curated data layers, semantic models, APIs, analytical models, and business-facing applications.
• Define non-functional requirements for security, privacy, performance, scalability, resiliency, observability, cost, and supportability.
• Establish reusable architecture and engineering patterns that can scale across Quality processes, sites, and global business teams.
• Apply modern engineering practices including source control, automated testing, CI/CD, secure development, deployment automation, and production monitoring.
• Evaluate technical options and make clear recommendations based on business value, delivery risk, lifecycle cost, and enterprise alignment.
• Ensure products progress beyond proof-of-concept work into governed, supported, and sustainable production capabilities.
• Architect and lead the delivery of Machine Learning, Generative AI, and Agentic AI solutions for Manufacturing and Quality.
• Design solutions using technologies such as large language models, embeddings, semantic search, vector stores, retrieval-augmented generation, knowledge graphs, orchestration frameworks, and AI agents.
• Develop capabilities such as signal detection, trend analysis, investigation support, regulatory intelligence, knowledge retrieval, summarization, recommendation generation, and workflow automation.
• Partner with Data Scientists and AI Engineers to define model workflows, evaluation approaches, prompt strategies, grounding methods, and human-in-the-loop controls.
• Determine when a business problem requires traditional analytics, Machine Learning, Generative AI, deterministic automation, or a combination of approaches.
• Design AI capabilities for traceability, explainability, evaluation, monitoring, and responsible use in Quality processes.
• Leverage enterprise AI platforms and reusable services where appropriate while ensuring solutions remain fit for their intended use.
• Evaluate emerging AI technologies through practical experimentation and apply them where they can create measurable business value.
• Help evolve products from descriptive reporting toward proactive intelligence, guided decision-making, and appropriately governed agentic workflows.
• Apply Quality Assurance experience to the design and delivery of solutions supporting regulated business processes.
• Partner with Quality process owners and subject matter experts to understand intended use, process controls, risk, records, approvals, and decision points.
• Ensure technical solutions account for data integrity, traceability, access control, change management, validation, and operational support requirements.
• Incorporate appropriate human review and approval controls where AI outputs inform Quality or compliance decisions.
• Work with Quality, Cybersecurity, GISQ, Software Assurance, validation, and Responsible AI teams to meet applicable governance requirements.
• Support Quality domains including Quality Management Systems, deviation management, CAPA, complaints, change control, audits, inspection readiness, quality risk management, laboratory operations, and batch release.
• Balance delivery speed with Quality, security, compliance, maintainability, and long-term business value.
• Lead product pods and guide engineers, data scientists, analysts, architects, and external partners through design, development, testing, deployment, and production support.
• Break complex problems into executable technical workstreams, milestones, dependencies, and delivery increments.
• Identify technical risks and integration constraints early and drive resolution across teams.
• Connect technical investments to measurable outcomes such as reduced manual effort, improved cycle time, earlier risk identification, stronger inspection readiness, and better decision-making.
• Challenge fragmented or overly customized approaches and recommend scalable capabilities that can be reused across the Manufacturing and Quality network.
• Serve as a trusted technical advisor to Manufacturing, Quality, Data, AI, and Technology leadership.
• Communicate technical decisions, risks, dependencies, and tradeoffs in clear business language.
• Provide technical oversight for work delivered by vendors, consulting partners, and system integrators.
• Mentor technical team members and help strengthen architecture, engineering, data, and AI capabilities across product teams.
• Maintain a strong quality bar while enabling teams to deliver iteratively and respond quickly to business feedback.

Benefits

• company bonus (depending, in part, on company and individual performance)
• company-sponsored 401(k)
• pension
• vacation benefits
• medical, dental, vision and prescription drug benefits
• flexible benefits (e.g., healthcare and/or dependent day care flexible spending accounts)
• life insurance and death benefits
• certain time off and leave of absence benefits
• well-being benefits (e.g., employee assistance program, fitness benefits, and employee clubs and activities)

What This Job Offers

• Job Type: Full-time
• Career Level: Senior