Principal AI/ML Engineer – Market Access

Eli Lilly and Company • Us, IN

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About The Position

The Lilly USA Tech@Lilly Market Access team is seeking a Principal AI/ML Engineer to build agentic AI and machine learning platforms for the Lilly Employer Organization. The role focuses on turning prototypes into reliable, scalable, well-governed production systems and developing reusable employer data pipelines, partner integrations, and ML engineering foundations.

The engineer will design and build orchestration frameworks, end-to-end data and model pipelines, serving infrastructure, and evaluation and monitoring capabilities. The work spans employer data, benefit administration, field operations, and third-party partner integrations. The engineer will partner with data scientists to productionize models and agentic workflows, and collaborate with the Employer Technical Product Manager, employer field teams, and Tech@Lilly colleagues to deliver secure, auditable applications. Reusable infrastructure and patterns are intended to make future employer workflows faster and less costly to deliver.

The role requires technical leadership and business analysis: engaging with business stakeholders, translating requirements between business and technical terms, defining requirements, involving appropriate business roles, participating in design reviews, and identifying opportunities to reuse services and processes. The position is full-time and requires authorization to work in the United States; Lilly will not sponsor work authorization or visas for this role. Travel is 0–10%.

Requirements

• Master’s degree in Computer Science, Computer Engineering, Data Science, Statistics, Mathematics, or another quantitative or technical field, plus at least 2 years of experience developing, deploying, or maintaining AI, machine learning, or data systems in production; OR bachelor’s degree in one of those fields plus at least 4 years of such experience.
• Authorization to work in the United States on a full-time basis; the employer will not sponsor work authorization or visas for this role.
• 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 stakeholders, translate requirements between business and technical terms, elicit and define requirements, and involve appropriate business roles in solution execution.
• Ability to participate in design reviews, collaborate with Tech@Lilly colleagues, identify reusable processes and services, and stay current with relevant tools and technologies.
• Ability to communicate with geographically dispersed business and technical colleagues and deliver reliable systems in complex data domains.

Nice To Haves

• Strong proficiency in Python and software-engineering practices, including version control, testing, and code review.
• Experience building and deploying data or ML systems in production.
• Experience engineering agent-to-agent orchestration and multi-agent workflow frameworks using tools such as LangGraph, LangChain, or equivalent, including tool/API integration and secure agent connectivity.
• Experience with 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 models and small specialized models, and fine-tuning and distillation pipelines.
• Experience building scalable data pipelines, using SQL and NoSQL data 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, PII, and data-residency constraints.
• Experience integrating external partner data and services, such as benefit administrators or health platforms, through APIs and secure data exchange.
• Understanding of U.S. employer healthcare, including employer-sponsored benefits, benefit design, payers, PBMs, and access models.
• Healthcare or pharmaceutical industry experience.
• 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, multi-agent workflow engines, tool and API integration layers, and secure connectivity to enterprise systems and external partners.
• Build and integrate secure, analytics-ready data pipelines using data from employers, benefit administrators, and third-party partners.
• Deliver AI capabilities for employer reporting, predictive analytics, benefit optimization, and decision support for employer field teams.
• Engineer production-scale end-to-end AI/ML pipelines covering data capture, feature engineering, training, fine-tuning, inference, and feedback.
• Establish ML engineering foundations such as model and prompt versioning, registries, experiment tracking, model CI/CD, automated evaluation, and rollback.
• Deploy production-grade model-serving systems using scalable serving, containerization, inference optimization, and in-house hosting of small specialized models, with attention to latency, cost, scalability, and data residency.
• Build AI-system observability and monitoring, including agentic workflow tracing, cost and latency tracking, drift detection, and production evaluation integration.
• Implement governance and data-protection controls for HIPAA 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.
• Communicate with technical and non-technical stakeholders and stay current with agentic AI and ML engineering tools.
• Manage and prioritize multiple projects simultaneously.
• Engage business stakeholders, identify opportunities to deliver business value, and translate business requirements and processes into technical solutions and vice versa.
• Elicit and define requirements, ensure appropriate business roles participate in solution execution, and participate in design reviews to maintain requirements traceability.
• Network with Tech@Lilly colleagues to determine solutions that meet business partners’ needs and identify reusable processes and services.
• Stay informed about tools and technologies to help influence Tech@Lilly strategy and business usage opportunities.

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 an employee assistance program, fitness benefits, and employee clubs and activities.

What This Job Offers

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