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.

Lead AI Data Engineer

eCTS · CTI-MD · Path/Level: R3

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Path/Level: R3

Note: Roles are posted at the lowest level of a band, however, employees should search across all levels of the band to identify all opportunities. Employees hired on banded positions (ex: P1–P3, R-path, B1–B3, etc.) transfer at their current level, despite the level indicated on the job posting. For example, if an R2 candidate is selected for an R1–R3 banded position, the candidate will remain an R2 in the new role.

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're looking for people who are determined to make life better for people around the world.

Role Overview

eCTS is a core clinical supply product within CTI-MD, helping make sure the right investigational medicine reaches the right patient at the right time. Over the next few years, clinical systems will evolve from a database-centric application into an intelligent, cloud-native clinical supply data platform: one where critical business logic is explicit and tested, data is served as governed products, and AI agents work safely alongside people to plan, monitor, and resolve supply events.

We are seeking a hands-on Data Systems Lead to drive that evolution. This role owns the data foundation of eCTS today, including the stored procedures and database objects that carry critical business logic, and leads its transformation into AI-enabled, full-stack flows, including the external facing site modernization. You will shape how data is structured, migrated, secured, served, and made AI-ready in a regulated pharmaceutical environment, while staying deeply hands-on with schema design, query optimization, migration, and troubleshooting, and setting standards the wider team can follow.

The person in this role will help build the following future state. It is the lens for every responsibility below.

Logic made explicit

Business rules held in legacy stored procedures are documented, covered by automated tests, and progressively re-platformed, with AI accelerating analysis and conversion under validated controls.

Data as a Service

eCTS data is published as governed, well-documented data products and APIs with clear contracts and SLAs, serving the application, analytics, adjacent clinical systems, and AI consumers.

AI-ready and agent-enabled

Data is structured, described, and exposed so AI agents can reason over it and act on it safely, with least-privilege access, human-in-the-loop approvals, and full auditability.

Cloud-native and as-code

Database changes, infrastructure, and quality checks flow through automated pipelines, with observability that moves operations from reactive to proactive.

What We're Really Looking For (Core Needs)

Two things matter most in this role:

• Ability to lead and technically execute agentic solutions independently. We have a strong and growing pipeline of agentic AI opportunities across eCTS, ranging from AI-assisted conversion of legacy logic to agents that surface, explain, and help resolve clinical supply and data issues. We need this person to lead and drive that space: to challenge and align platform-level teams, set technical direction, and execute hands-on without hand-holding. This is an autonomous, get-it-done technical leadership role, not a coordination-only one.

• Genuine passion for the core database work. eCTS's stored procedures and database objects encode years of clinical supply know-how and remain a key contributor to the product today. This role owns that work end to end: enhancing it, continuously improving it, and actively using AI to convert these legacy flows into future-state full-stack and AI-enabled flows. We need someone who values this foundation, takes pride in keeping it healthy and reliable, and is energized by both mastering the existing logic and leading its transformation, not just by greenfield modernization.

What You Will Do

Database Design & Development

• Own, maintain, and continuously improve eCTS's existing stored procedures and database objects, which carry critical business logic today, while leading their conversion into full-stack and AI-enabled flows using AI-assisted approaches.

• Make embedded business logic explicit: document rules, build automated unit and regression tests for stored procedures and data logic, and create the safety net that makes confident, rapid change possible.

• Own the design, development, and evolution of relational and non-relational data models supporting eCTS and IWRS.

• Write, review, and optimize complex SQL, stored procedures, functions, and scripts, with the depth and care to keep long-standing logic correct and performant.

• Translate product and engineering requirements into robust, scalable database designs.

• Establish and enforce data modeling standards, naming conventions, and design patterns across the team.

Database Modernization & Migration

• Lead the technical execution of the eCTS database modernization strategy, moving from legacy databases to a modern, cloud-native data platform.

• Design and deliver migration approaches (schema conversion, data mapping, ETL/ELT pipelines, and cutover plans) that minimize disruption to global trial operations.

• Apply AI-assisted tooling to schema conversion, code translation, and data reconciliation, with evaluation and human review built into the process.

• Design for decoupling, using event-driven and change-data-capture (CDC) patterns so IWRS and downstream consumers can evolve independently.

• Partner with architects to evaluate target database technologies, trade-offs, and integration patterns.

• De-risk migration through prototypes, dry runs, reconciliation, and rollback planning.

Data Products & AI Readiness

• Design eCTS data as reusable data products with clear ownership, documentation, data contracts, and SLAs, in line with the CTI-MD Data as a Service (DaaS) direction.

• Build the metadata, lineage, and semantic context that let people and AI systems find, understand, and trust eCTS data.

• Expose governed data access for applications and AI agents through APIs and agent tooling (for example, Model Context Protocol servers), with least-privilege and auditable access patterns.

• Apply retrieval and vector search patterns (for example, embeddings in PostgreSQL) where they add real value to search, support, and decision-making.

Agentic AI & Technical Innovation

• Lead and drive the exploration and delivery of agentic AI solutions across eCTS, working from a strong and growing opportunity pipeline.

• Set technical direction, prototype, and execute agentic solutions hands-on, independently and without hand-holding.

• Build the evaluation, guardrail, and observability practices that make agents trustworthy in a regulated setting: test sets, quality metrics, human-in-the-loop approval for consequential actions, and full traces of agent behavior.

• Challenge, influence, and align platform-level teams to unblock and advance agentic initiatives.

• Bring a builder's bias: turn ideas and POCs into working, production-ready capabilities, and keep pace with fast-moving AI practices and tools.

Technical Leadership

• Act as the technical point of reference for all database and data platform matters on eCTS.

• Guide engineers on data design decisions, performance tuning, and best practices, including how to work effectively with AI coding and data tools.

• Review database changes and pull requests, ensuring quality, consistency, and maintainability.

• Balance long-term data architecture health against near-term delivery needs.

Engineering Excellence

• Treat the database as code: version-controlled schema and logic, automated migrations, and database changes delivered through CI/CD with automated quality gates.

• Use infrastructure as code and repeatable environments to make development, testing, and validation faster and more consistent.

Performance, Reliability & Operations

• Monitor, diagnose, and tune database performance: indexing, query plans, partitioning, and capacity.

• Ensure high availability, backup/recovery, and disaster-recovery readiness for eCTS data.

• Define service-level objectives and data observability so issues are detected and addressed before they affect trial operations.

• Partner with support and operations teams to resolve production data issues and prevent recurrence.

• Build AI-enabled monitoring and operational tooling, such as anomaly detection and assisted root-cause analysis, that improves database observability and support.

Data Integrity, Security & Compliance

• Ensure database solutions meet GxP, data integrity (ALCOA+), validation, and audit requirements.

• Apply risk-based assurance approaches, including Computer Software Assurance (CSA), and support the risk-proportionate data governance expected under ICH E6(R3).

• Define how AI-assisted changes and agent actions are validated, reviewed, and recorded, and stay current with emerging regulatory expectations for AI in GxP environments.

• Implement data security, access controls, encryption, and data-retention practices in line with Lilly policy and regulatory expectations.

• Maintain documentation and traceability required for validated, regulated systems.

Collaboration & Delivery

• Partner with the eCTS Product Manager, engineers, architects, and quality teams throughout the delivery lifecycle.

• Contribute to backlog refinement, estimation, and sprint delivery in an Agile environment.

• Support incremental, release-based delivery, contributing database work across successive releases without regressions.

Knowledge Sharing & Mentoring

• Coach and mentor engineers on database design, performance, modernization, and AI-enabled engineering practices.

• Share domain and technical knowledge to raise the overall data and AI capability of the team.

• Bring a no-ego, team-first mindset, prioritizing shared success over individual recognition.

Your Minimum Required Qualifications

Education

• Bachelor's degree in Computer Science, Engineering, Information Systems, or a related technical discipline.

Experience

• 6+ years of hands-on database engineering / development experience.

• Experience leading database design and development on non-trivial software products.

• Experience delivering data migration or database modernization efforts.

• Experience working with engineering teams in Agile environments.

Technical Skills

• Strong SQL and relational database expertise (e.g., SQL Server, Oracle, PostgreSQL, or equivalent), including performance tuning and query optimization.

• Deep, hands-on comfort with stored procedures and complex database logic, and a genuine willingness to own and improve long-standing legacy objects.

• Solid data modeling skills across transactional and analytical use cases.

• Experience with ETL/ELT and data migration tooling and patterns.

• Working knowledge of cloud data platforms (Azure and/or AWS) and modern managed database services.

• Understanding of database security, high availability, backup/recovery, and monitoring.

• Hands-on experience building AI- or LLM-enabled solutions (for example, agents, retrieval, or AI-assisted code and data workflows), including at least one used by others beyond a personal prototype.

• Experience with database-as-code practices: source control, CI/CD, automated migrations, and database change management.

• Ability to read and reason about application code well enough to partner effectively with engineers on data-related issues.

Leadership Behaviors

• Demonstrated ability to work autonomously, driving technical initiatives end to end and influencing other teams without relying on close direction.

• Comfort making sound decisions with incomplete information in a fast-moving technology space, and learning quickly as tools and practices evolve.

What You Should Bring

• Experience in Pharmaceutical, Life Sciences, Clinical Development, Supply Chain, or Regulatory / Quality domains.

• Understanding of GxP, validation, data integrity, and regulated environments, including risk-based approaches such as Computer Software Assurance.

• Experience with clinical, manufacturing, or laboratory systems (e.g., IWRS / clinical supply systems).

• Experience with agent frameworks, Model Context Protocol, LLM evaluation, or AI observability tooling.

• Experience with automated database testing and migration tools (e.g., tSQLt, pgTAP, Flyway, Liquibase) and infrastructure as code.

• Familiarity with event streaming and CDC, NoSQL, vector databases, lakehouse platforms (e.g., Databricks), or analytics platforms.

• Relevant database, cloud, or AI certifications are a plus.

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