Eli Lilly
Pharma · Pharma
- HQ
- Indianapolis, US
- Founded
- 1875
- Size
- 35,000+
- Website
- lilly.com
Currently tracking 28 active AI roles, down 25% versus the prior 4 weeks. Primary focus: Agent · Engineering. Salary range $58k–$345k (avg $175k).
Eli Lilly currently has 36 active AI-related job listings. The majority of these roles, 56%, are focused on agents, with data-related positions making up another 28%. Engineering is the most frequent function for these hires. The company is primarily hiring in the United States and India. Frequent technology tags include agent orchestration, RAG, and model serving, indicating a focus on building and deploying AI systems.
Eli Lilly currently has 36 active AI-related roles in our index. The most common open titles are: Director, Discovery Bioinformatics Oncology (2), Advisor - Agent Research, Advisor - Antibody Developability Validation & Benchmarking, Advisor - Data Architect, Data Foundry, Advisor - Lab Automation Software Engineer. Most positions are in Engineering and Research.
Eli Lilly's active AI hiring is concentrated in: agents (53%), data (25%), application (8%). These categories follow a seven-stage AI lifecycle: data, pre-training, post-training, serving infrastructure, agents, evaluation, and application.
Eli Lilly is hiring AI talent in: United States (29 roles), India (7 roles).
Job postings at Eli Lilly most frequently reference: agent orchestration, rag, model serving, llm observability, vector db.
In the past 30 days, Eli Lilly has posted 12 new AI-related roles. That is a -48% change versus the prior 30 days (23 → 12).
| Title | Stage | AI score |
|---|---|---|
| Associate Vice President - Methods4Insight, Data Foundry Associate Vice President leading the analytical methods and computational science pillar within Data Foundry, focusing on accelerating molecule discovery. This role involves leading a team of experts in cheminformatics, computational structural biology, statistical modeling, and AI/ML, ensuring Lilly has access to advanced analytical approaches for both human scientists and AI agents. The position requires strategic decision-making on adopting or developing methods, identifying data gaps, and establishing validation frameworks, with a strong emphasis on integrating methods into AI agent workflows. | DataAgent | 8 |
| Post Doctoral Scientist – Human Genomics and Translational Data Sciences This role focuses on applying statistical and computational approaches, including machine learning, to analyze large-scale multi-omics (genomic, proteomic, metabolomic) and clinical data from biobanks and population cohorts. The goal is to identify novel therapeutic targets and biomarkers for cardiometabolic diseases. The role involves developing and implementing bioinformatics pipelines, contributing to novel statistical methods, and collaborating with interdisciplinary teams to guide therapeutic development. While the primary focus is on data analysis and method development (L0/L2), the ultimate aim is to inform drug discovery and development. |
| DataPost-train |
| 7 |
| CADD Postdoctoral Scientist Postdoctoral Scientist role focused on developing synthesis-aware virtual screening workflows for early small-molecule drug discovery, integrating AI/ML with structure-based drug design and fragment chemistry. | Data | 7 |
| Director/Senior Director, ADMET & PK/PD Modeling This role focuses on building and validating predictive models for ADMET and PK/PD endpoints within a healthcare AI/ML platform for drug discovery. It involves developing translational and distribution modeling approaches, ensuring model usability for partners, defining data strategies, and leveraging AI/agentic tools for automation and interpretability. The role also includes mentorship of junior scientists. | Data | 7 |
| Scientific Lead - Scientific Data Engineer This role focuses on building the data infrastructure and semantic layer to make scientific data accessible for AI systems, specifically for drug discovery research. It involves designing and building data architectures, ETL/ELT pipelines, and AI-ready data products, including vector embedding pipelines for RAG. The role bridges data infrastructure and generative AI engineers, aiming to convert early deployments into repeatable system standards and evaluation practices. | DataAgent | 7 |
| Advisor, Data Scientist - CMC Data Products The role focuses on developing and delivering enterprise-scale data products that power AI-driven insights, process optimization, and regulatory compliance within the pharmaceutical domain. It involves defining data archetypes, creating reusable data models, and implementing data frameworks for regulated environments. The core responsibility is building AI-ready data products, including training datasets for various AI/ML applications and supporting generative AI for knowledge management. | Data | 7 |
| Advisor - Data Architect, Data Foundry The Data Architect will design and build the data infrastructure for AI-native drug discovery, focusing on data modeling, lakehouse architecture, and knowledge graphs. This role transforms raw scientific data into machine-actionable assets for scientists and AI agents, supporting model training and RAG workflows. | DataAgent | 5 |
| Data Architect, Data Foundry Seeking Data Architects to design and build the data infrastructure for AI-native drug discovery. This involves creating schemas, ontologies, data models, and platform architectures to transform raw scientific data into machine-actionable assets for discovery scientists and autonomous AI agents. The role focuses on data modeling, data platform architecture, and knowledge graph systems, enabling AI-driven capabilities. | DataAgent | 5 |
| Director/Sr Director Pharmacometrics Director/Sr Director Pharmacometrics role at Eli Lilly focused on advancing drug discovery and development through quantitative science, with a strong emphasis on integrating AI/ML and automation into modeling workflows. The role involves scientific and technical leadership, mentoring, and shaping PMx strategy across programs and the organization, including engagement with regulatory agencies. | Data | 5 |