Principal AI/ML Engineer – Data Analytics & AI

Lilly • Indianapolis, IN

1d • $69,000 - $165,000

About The Position

Lilly USA Technology at Lilly’s Data Analytics & AI team is seeking a Principal AI/ML Engineer to build agentic AI and machine-learning platforms that turn prototypes into reliable, scalable, well-governed production systems. The role builds reusable data pipelines, partner integrations, and ML engineering foundations that support business use cases across Lilly USA.

The engineer will design and build orchestration frameworks, end-to-end data and model pipelines, serving infrastructure, and evaluation and monitoring systems. The role works across enterprise data, business operations, field and customer-facing teams, and third-party integrations, partnering with data scientists, technical product managers, business teams, and Technology at Lilly colleagues to deliver secure, auditable applications. The goal is to create reusable infrastructure and patterns that make subsequent use cases faster and less costly to deliver.

Potential applications include agentic workflows for field and commercial teams, predictive models for market access and resource allocation, retrieval-augmented generation solutions grounded in trusted sources, secure partner-data pipelines, and shared AI tooling for deployment, evaluation, and monitoring. The position supports Lilly’s purpose of creating medicines that make life better and the Lilly USA team’s work to improve medicine access, affordability, customer engagement, and patient outcomes.

The anticipated wage is $69,000–$165,000. Full-time equivalent employees are eligible for a company bonus, depending in part on company and individual performance, and eligible employees may participate in Lilly’s comprehensive benefits program. Travel is 0–10%.

Requirements

• Master’s degree in Computer Science, Computer Engineering, Data Science, or a related quantitative or technical field, plus at least 1 year of professional experience implementing technical systems; or a bachelor’s degree in one of these fields plus at least 3 years of such experience.
• Foundational knowledge of communication, leadership, teamwork, problem solving, solution and blueprint definition, business acumen, architectural processes, technical standards, project delivery, and the industry.
• Ability to engage business partners, understand requirements, and translate between business needs and technical solutions.
• Qualified applicants must be authorized to work in the United States on a full-time basis; Lilly will not sponsor or support work authorization or visas for this role.

Nice To Haves

• Strong proficiency in Python and sound software-engineering practices, including version control, testing, and code review.
• Experience taking machine-learning or data solutions from idea through production deployment and working with business users to drive adoption.
• Experience with end-to-end ML engineering, including model and prompt versioning, registries, experiment tracking, model CI/CD, automated pipeline evaluation, and AI-system observability.
• Experience with scalable model serving, containerization, inference optimization, serving large and small specialized models, and fine-tuning and distillation pipelines.
• Experience engineering agent-to-agent orchestration and multi-agent workflow frameworks using modern tooling such as LangGraph, LangChain, or equivalent, including tool and API integration and secure agent connectivity.
• Experience building scalable data pipelines and working with SQL and NoSQL stores, distributed processing, vector databases, and retrieval systems.
• Experience with AWS or Azure, Databricks, containers, Git, and CI/CD automation.
• Experience building secure, auditable systems and handling PHI and PII while respecting data-residency constraints.
• Experience integrating external partner data and services through APIs and secure data exchange.
• Familiarity with the U.S. healthcare and pharmaceutical landscape, including payers, providers, PBMs, and patient access, or the ability to ramp quickly in a complex, regulated domain. Healthcare or pharma experience is a plus.
• Demonstrated ability to deliver reliable systems in complex data domains and communicate with geographically dispersed business and technical colleagues.

Responsibilities

• Build and operationalize agentic AI platforms, including agent-to-agent orchestration frameworks, multi-agent workflow engines, tool and API integration layers, and secure connectivity to enterprise systems and external partner platforms.
• Build and integrate data pipelines that bring enterprise, vendor, and third-party partner data into secure, analytics-ready platforms.
• Deliver AI capabilities for business use cases, including reporting, predictive analytics, process and decision optimization, and decision support for field and commercial teams.
• Engineer end-to-end AI/ML pipelines covering data capture, feature engineering, training, fine-tuning, inference, and feedback at production scale.
• Establish ML engineering foundations, including model and prompt versioning, registries, experiment tracking, model CI/CD, automated evaluation, and rollback.
• Deploy scalable model-serving infrastructure using techniques such as containerization and inference optimization, with attention to latency, cost, scalability, and data residency.
• Build observability and monitoring for AI systems, including agent-workflow tracing, cost and latency tracking, drift detection, and production AI evaluation.
• Implement governance and data-protection controls, including privacy and regulatory compliance, PHI and PII handling, de-identification, and auditability.
• Design reusable, horizontal engineering capabilities and shared infrastructure for multiple teams and use cases.
• Partner with data scientists to productionize prototypes and improve their scale, reliability, and maintainability; work with business users to drive adoption.
• Communicate with technical and non-technical stakeholders and stay current with emerging agentic AI and ML engineering tools.
• Manage and prioritize multiple projects simultaneously.
• Engage with business partners to identify opportunities to deliver business value and translate business needs and processes into technical requirements, and vice versa.
• Elicit and define requirements, ensure relevant business roles are engaged in solution execution, and participate in design reviews to maintain requirements traceability.
• Collaborate with Technology at Lilly colleagues to determine solutions that meet business needs and seek opportunities to reuse processes and services.
• Stay abreast of tools and technologies to help inform Technology at Lilly strategy and business opportunities.

Benefits

• Company bonus eligibility for full-time equivalent employees, 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 an employee assistance program, fitness benefits, and employee clubs and activities.

What This Job Offers

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