Data & AI Architect

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. 

The Data & AI Architect is a senior Tech at

Lilly role built on a foundational conviction: advanced analytics and AI systems are only as capable as the data foundations beneath them. At the RTP digital manufacturing site, this role is responsible for designing and governing the data architecture that makes analytics and AI adoption possible, scalable, and trustworthy — from manufacturing execution and quality systems to predictive analytics and adaptative workflows.

The role spans two interconnected domains. As Data Architect, the incumbent follows, and provides input to, MQ standards for data models, integration patterns, governance structures, and cloud platform standards that enable a reliable and scalable AI-ready data foundation. As AI Architect, the incumbent translates that foundation into deployable AI capabilities: evaluating tools and platforms, designing human-in-the-loop workflows for GMP contexts, and ensuring AI outputs are reproducible, auditable, and fit for a regulated manufacturing environment.

RTP is positioned as a digital-native site within Lilly, meaning it brings a data rich environment and business areas primed for leveraging that data. The Data & AI Architect role is a cornerstone of that positioning — setting patterns that will influence the broader network while being directly accountable for RTP’s operational excellence.

Responsibilities:

AI-Ready Data Architecture

·         Maintain the RTP site data architecture, including canonical data models for manufacturing (batch, equipment, process parameters), quality (deviations, CAPAs, specifications), quality control (methods, samples, results), and supply chain domains.

·         Adopt global MQ data integration strategies and architectures and influence the evolution of those strategies to enable RTP-specific downstream AI/ML and analytics use cases.

·         Establish and maintain naming conventions, metadata standards, and master data governance frameworks to ensure data is clean, consistent, and AI-consumable at source.

·         Own data lifecycle policies covering retention, archival, lineage tracking, and GMP data integrity compliance (ALCOA+ principles) across all site data domains. Align these policies with Manufacturing and Quality standards.

·         Ensure RTP’s data platform architecture aligns with Lilly enterprise cloud standards (Azure/AWS) while remaining fit for the operational realities of a manufacturing site.

AI Systems Architecture & Platform Design

·         Define the AI platform architecture for the site, including how enterprise AI capabilities (Copilot, Claude-based agentic tools, Coretex) are configured, integrated, and governed at the site layer.

·         Architect AI-enabled workflows for high-value manufacturing and quality use cases: LLM-assisted batch record review, materials management, predictive maintenance, visual inspection, and electronic logbook analysis.

·         Design prompt engineering standards, retrieval-augmented generation (RAG) patterns, and grounding strategies that connect LLMs to site-specific structured and unstructured data.

·         Define agentic workflow boundaries for GMP contexts: where AI acts autonomously, where human review is mandatory, and how decisions are logged for auditability.

·         Evaluate and select AI/ML tools, vendor solutions, and platform integrations relevant to pharmaceutical manufacturing; provide architectural recommendations to site and network leadership.

·         Deploy enterprise standard platforms and tools to deliver RTP use cases.

Data Governance & AI Governance

·         Establish the RTP data governance framework, including the data stewardship model, data quality KPIs, issue resolution processes, and periodic review cadence.

·         Establish the RTP AI solution framework, defining development lifecycle milestones, roles and responsibilities.

·         Define the site AI governance framework, covering use-case risk classification, model performance monitoring, drift detection, and periodic review of deployed AI systems.

·         Ensure all data and AI implementations comply with Lilly information security and GxP data integrity requirements.

·         Maintain appropriate documentation for AI systems used in or adjacent to regulated processes; support computerized system validation (CSV/GAMP5) activities for AI-enabled tools.

·         Serve as the site’s primary interface for data and AI-related audits, regulatory inspections, and technical review boards.

Site & Network Influence

·         Act as the RTP representative in Lilly enterprise data and AI architecture forums; contribute RTP patterns as reusable reference architectures for the broader PDN network.

·         Partner across peer manufacturing sites and with global MQ partners to identify shared data challenges, harmonize ontologies, and promote consistent AI deployment patterns across the network.

·         Partner with site cross-functional teams (e.g. engineering) to ensure AI and analytics roadmaps align with established architectures and solution footprint standards.

·         Continuously scan the pharmaceutical AI landscape and interface with 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 clearly to site leadership, Tech@Lilly management, and cross-functional business 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 business stakeholders to identify opportunities to maximize value through digitization, analytics, and AI.

Champion best practices within the RTP site

·         Build data and AI literacy among site teams by translating architectural choices into practical guidance for engineers, quality professionals, and operators who interact with AI-enabled tools.

·         Mentor junior data and digital team members on data modelling, integration patterns, and responsible AI deployment principles.

·         Define and track KPIs for data quality, platform reliability, and use-case value realization. Report outcomes to site and Tech@Lilly leadership.

Basic Qualifications:

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

Additional Skills / Preferences:

• 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 (LangChain, AutoGen, Claude tool-use API, or equivalent).
• Proficiency in data modelling methodologies (3NF, dimensional modelling, ontology/semantic graph).  
• Familiarity with Lilly enterprise platforms: MES (Pharmasuite or equivalent), LIMS (Labvantage), SAP, QDS (Veeva Vault), Jira, Smartsheet.
• AWS Solutions Architect or Azure Data/AI Engineer certification; CDMP or equivalent data governance certification.
• Knowledge of GMP data integrity requirements (ALCOA+). 
• Previous IT/technical leadership experience in a pharmaceutical manufacturing network.

Additional Information:

·         Travel Percentage (%): 10%

·         Shift Information: Day Shift

NOTE: This job description is intended to provide a general overview of the job requirements at the time it was prepared. The job requirements of any position may change over time and may include additional responsibilities not specifically described in the job description. For GMP purposes, the job description should be updated for significant changes. As always, you should consult with your supervisor regarding your actual job responsibilities and any related duties that may be required for the position.

Lilly is dedicated to helping individuals with disabilities to actively engage in the workforce, ensuring equal opportunities when vying for positions. If you require accommodation to submit a resume for a position at Lilly, please complete the accommodation request form (https://careers.lilly.com/us/en/workplace-accommodation) for further assistance. Please note this is for individuals to request an accommodation as part of the application process and any other correspondence will not receive a response.

Lilly is proud to be an EEO Employer and does not discriminate on the basis of age, race, color, religion, gender identity, sex, gender expression, sexual orientation, genetic information, ancestry, national origin, protected veteran status, disability, or any other legally protected status.

Our employee resource groups (ERGs) offer strong support networks for their members and are open to all employees. Our current groups include: Africa, Middle East, Central Asia (AMECA), Black Employees at Lilly (BE@Lilly), Chinese Culture Network (CCN), EnAble, Evolve, Lilly Indian Network (LIN), Organization of Latinx at Lilly (OLA), Pride (LGBTQ+ Allies), Veterans Leadership Network (VLN) and Women’s Initiative for Leading at Lilly (WILL).

Actual compensation will depend on a candidate’s education, experience, skills, and geographic location.  The anticipated wage for this position is

Full-time equivalent employees also will be eligible for a company bonus (depending, in part, on company and individual performance). In addition, Lilly offers a comprehensive benefit program to eligible employees, including eligibility to participate in a company-sponsored 401(k); pension; vacation benefits; eligibility for 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; and well-being benefits (e.g., employee assistance program, fitness benefits, and employee clubs and activities).Lilly reserves the right to amend, modify, or terminate its compensation and benefit programs in its sole discretion and Lilly’s compensation practices and guidelines will apply regarding the details of any promotion or transfer of Lilly employees.

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