Data & AI Architect

Lilly • Durham, NC

13d • $129,000 - $211,200

About The Position

The Data & AI Architect is a senior Tech at Lilly role responsible for designing and governing the data architecture that enables scalable, reliable, and trustworthy analytics and AI at Lilly’s RTP digital manufacturing site. The role covers manufacturing, quality, quality control, and supply chain data, and establishes patterns intended to support RTP’s operational excellence and influence the broader network.

As Data Architect, the role follows and provides input to MQ standards for data models, integration patterns, governance, and cloud platforms. As AI Architect, it translates the data foundation into deployable AI capabilities by evaluating tools and platforms, designing human-in-the-loop workflows for GMP contexts, and ensuring AI outputs are reproducible, auditable, and appropriate for regulated manufacturing.

The position defines site data and AI architectures, governance frameworks, and implementation practices; supports compliance with information security and GxP data integrity requirements; and serves as the site interface for audits, regulatory inspections, and technical review boards. It represents RTP in enterprise architecture forums, partners with site and network stakeholders, leads AI adoption, builds data and AI literacy, mentors junior team members, and tracks architecture and use-case outcomes. The role is a day-shift position with 10% travel.

Requirements

• Bachelor’s degree in Computer Science, Information Technology, Engineering, or a related technical field.
• At least 8 years of experience in data architecture, data engineering, or technology roles.
• At least 3 years of experience in a manufacturing or pharmaceutical operations context.
• Fluent English.
• Practical working knowledge of large language models, prompt engineering, and AI architectures with appropriate human-in-the-loop controls.
• Proficiency in data integration patterns, including ETL/ELT, API-based, and event-driven patterns.
• Experience with cloud data platforms such as Azure or AWS.
• Knowledge of computerized system validation (CSV) and GAMP5.
• Ability to communicate complex data and AI concepts to non-technical stakeholders and influence cross-functional teams without direct authority.

Nice To Haves

• Master’s degree in Computer Science, Data Science, Information Systems, or Engineering.
• Experience in a manufacturing site environment.
• Comfort with ambiguity and building from scratch.
• Hands-on experience with agentic AI development frameworks such as LangChain, AutoGen, Claude tool-use API, or equivalent.
• Proficiency in data modelling methodologies such as 3NF, dimensional modelling, and ontology/semantic graph.
• Familiarity with Lilly enterprise platforms: MES (Pharmasuite or equivalent), LIMS (Labvantage), SAP, QDS (Veeva Vault), Jira, and Smartsheet.
• AWS Solutions Architect or Azure Data/AI Engineer certification; CDMP or equivalent data governance certification.
• Knowledge of GMP data integrity requirements, including ALCOA+.
• Previous IT/technical leadership experience in a pharmaceutical manufacturing network.

Responsibilities

• Maintain RTP site data architecture, including canonical data models for manufacturing, quality, quality control, and supply chain domains.
• Adopt global MQ data integration strategies and architectures and influence their evolution to support RTP downstream AI/ML and analytics use cases.
• Establish naming conventions, metadata standards, and master data governance frameworks to ensure data is clean, consistent, and AI-consumable at source.
• Own data lifecycle policies for retention, archival, lineage tracking, and GMP data integrity compliance, aligning them with Manufacturing and Quality standards.
• Ensure RTP data platform architecture aligns with Lilly enterprise cloud standards, including Azure and AWS, and manufacturing-site operational needs.
• Define the site AI platform architecture and how enterprise AI capabilities and tools are configured, integrated, and governed at the site layer.
• Architect AI-enabled workflows for manufacturing and quality use cases, including batch record review, materials management, predictive maintenance, visual inspection, and electronic logbook analysis.
• Design prompt engineering standards, RAG patterns, and grounding strategies connecting LLMs to site-specific structured and unstructured data.
• Define agentic workflow boundaries for GMP contexts, including autonomy, mandatory human review, and decision logging for auditability.
• Evaluate AI/ML tools, vendor solutions, and platform integrations for pharmaceutical manufacturing and provide architectural recommendations to site and network leadership.
• Deploy enterprise-standard platforms and tools to deliver RTP use cases.
• Establish the RTP data governance framework, including data stewardship, data quality KPIs, issue resolution processes, and periodic reviews.
• Establish the RTP AI solution framework, including development lifecycle milestones, roles, and responsibilities.
• Define site AI governance covering use-case risk classification, model performance monitoring, drift detection, and periodic review of deployed systems.
• Ensure data and AI implementations comply with Lilly information security and GxP data integrity requirements.
• Maintain documentation for AI systems used in or adjacent to regulated processes and support CSV/GAMP5 activities for AI-enabled tools.
• Serve as the site’s primary interface for data and AI audits, regulatory inspections, and technical review boards.
• Represent RTP in Lilly enterprise data and AI architecture forums and contribute reusable reference architectures for the broader PDN network.
• Partner with peer manufacturing sites and global MQ partners to address shared data challenges, harmonize ontologies, and promote consistent AI deployment patterns.
• Partner with site cross-functional teams, including engineering, to align AI and analytics roadmaps with established architectures and solution footprint standards.
• Monitor developments in pharmaceutical AI and engage external thought leaders and technology vendors to bring relevant advances to the site and network.
• Communicate architecture decisions, data strategy progress, and AI adoption status to site leadership, Tech@Lilly management, and cross-functional partners.
• Act as the site AI ambassador and lead AI adoption across site functions.
• Develop an in-depth understanding of site business processes and work with stakeholders to identify digitization, analytics, and AI opportunities.
• Build data and AI literacy by translating architectural choices into practical guidance for engineers, quality professionals, and operators.
• Mentor junior data and digital team members on data modelling, integration patterns, and responsible AI deployment.
• Define and track KPIs for data quality, platform reliability, and use-case value realization, and report outcomes to site and Tech@Lilly leadership.

Benefits

• Company bonus, depending in part on company and individual performance.
• Eligibility to participate in a company-sponsored 401(k).
• Pension.
• Vacation benefits.
• Eligibility for medical, dental, vision, and prescription drug benefits.
• Flexible benefits, including 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, including employee assistance, fitness benefits, and employee clubs and activities.

What This Job Offers

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