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.
We are looking for a Senior Principal Machine Learning Engineer to join the AI Engineering team, with a primary focus on Hands-On Engineering (MLE) and MLOps & Platform Reliability and GenAI & Agentic Systems. This posting is at level R4 on our engineering ladder — see the level framing below for the expected scope of ownership and impact.
Level framing: Recognized expert who mentors others; makes key technical decisions impacting multiple teams; leads resolution of highly complex challenges; cross-functional influence; may engage with external partners as an authority.
- Design and build production backend systems for agentic AI applications — API layers, backend-for-frontend (BFF) patterns, session/state management, and streaming for concurrent multi-user workloads.
- Lead resolution of highly complex, cross-system technical challenges.
- Set the technical bar for hands-on engineering practice across the team.
- Own GitOps and engineering-governance standards across the team (version control, CI/CD, review, promotion).
- Make key MLOps/platform decisions that affect multiple teams (e.g. deployment topology, observability strategy).
- Drive triage and resolution of complex, cross-system production incidents.
- Own architecture for agentic AI systems, including routing, policy enforcement, and RAG/knowledge-registry design.
- Lead evaluation and adoption of new agent frameworks, LLMOps practices, and GenAI tooling across the team.
- Implement authentication/authorization flows for agentic systems (OAuth/OIDC, on-behalf-of token exchange, secure credential storage).
- Mentor other engineers on architecture, design patterns, and production engineering practices, and act as a role model for engineering rigor across the wider team.
- Cloud & Data Infra: AWS (EC2/ECS, S3, Lambda, IAM, CloudWatch or equivalent); Databricks & Unity Catalog
- Foundational: Python; Git/GitHub; software engineering best practices; testing; SQL
- MLOps & Deployment: Docker, Kubernetes, Prefect; CI/CD (GitHub Actions); production monitoring; model versioning & lineage; GitOps governance
- GenAI & Agentic Architecture: Claude or comparable LLMs; LangGraph or comparable agent frameworks; RAG architectures; vector databases (e.g. Pinecone); prompt engineering & evaluation
11–15 years of hands-on experience, with demonstrated growth into architecture-level ownership spanning multiple teams or systems.
- Strong proficiency in Python and a track record of writing clean, testable, production-quality code.
- Demonstrated experience owning CI/CD, containerisation, and orchestration for production ML/AI systems.
- Proven experience developing or deploying LLM-based applications, including prompt engineering, RAG, or agentic workflows.
- Strong working knowledge of containerisation (Docker), orchestration (Kubernetes), and CI/CD pipelines.
- Working knowledge of AWS cloud services and Databricks/Unity Catalog or equivalent enterprise data platforms.
- Excellent verbal and written communication skills.
- Experience working in Agile/Scrum environments.
Bachelor's or Master's degree in Computer Science, Computer Applications, or a related technical field.
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 does not discriminate on the basis of age, race, color, religion, gender, sexual orientation, gender identity, gender expression, national origin, protected veteran status, disability or any other legally protected status.
#WeAreLillySkills Required
- 11-15 years of hands-on experience with architecture-level ownership across multiple teams or systems
- Bachelor's or Master's degree in Computer Science, Computer Applications, or a related technical field
- Strong proficiency in Python and experience writing clean, testable, production-quality code
- Experience owning CI/CD, containerization, and orchestration for production ML/AI systems
- Experience developing or deploying LLM-based applications, including prompt engineering, RAG, or agentic workflows
- Strong working knowledge of Docker, Kubernetes, and CI/CD pipelines
- Working knowledge of AWS cloud services and Databricks/Unity Catalog or equivalent enterprise data platforms
- Excellent verbal and written communication skills
- Experience working in Agile/Scrum environments
Eli Lilly and Company Compensation & Benefits Highlights
The following summarizes recurring compensation and benefits themes identified from responses generated by popular LLMs to common candidate questions about Eli Lilly and Company and has not been reviewed or approved by Eli Lilly and Company.
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Retirement Support — Feedback suggests long-term savings are bolstered by a defined-benefit pension alongside a company 401(k) match and retiree health options. These elements make total compensation feel strong beyond base salary.
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Leave & Time Off Breadth — Feedback suggests paid time off is expansive, with substantial vacation, company shutdown days, and milestone time. This breadth of leave is viewed as a meaningful part of overall rewards.
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Parental & Family Support — Feedback suggests family-building and caregiving support are robust, including paid parental leave, adoption or surrogacy assistance, and backup care. These programs enhance the perceived value of benefits across life stages.
Eli Lilly and Company Insights
What We Do
Eli Lilly and Company engages in the discovery, development, manufacture, and sale of products in pharmaceutical products business segment. For more than a century, we have stayed true to a core set of values – excellence, integrity, and respect for people – that guide us in all we do: discovering medicines that meet real needs, improving the understanding and management of disease, and giving back to communities through philanthropy and volunteerism.
