Applied AI Engineer, Clinical Informatics

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.  Therapy areas across Eli Lilly focus on new therapeutic approaches for the treatment of different diseases. You will work with partners across Lilly to discover and develop novel biologic, small molecule and nucleic acid-based therapeutics. Our focus is the patient: by understanding the biology and pathophysiology underlying disease states, we aim to address the root cause of disease and develop breakthrough therapies. We have one of the strongest pipelines in the industry and a track record of delivering impactful medicines that improve people’s lives. The Lilly research environment is evolving to centralize the access and analysis of human genetic, omic, and clinical data. This new initiative will work to define data, tools and process to provide the therapy area teams key evidence for target evaluation and target discovery.   We are seeking a highly specialized Applied AI Engineer Clinical Informatician to lead research at the intersection of completed clinical trial datasets and biobank-linked population data. This is fundamentally a hands-on research role (not operational trial management), where you will be an individual contributor. Your core mission is to build the systems and tools that extract, define, and contextualize patient phenotypes from locked trial databases, real-world data, and biobank cohorts, that will turn archived data that can generate translational insight that shapes the next generation of clinical research.   You will work with rich, already-collected datasets: locked trial databases, archived omics profiles, longitudinal electronic health records, and population-scale biobank cohorts. Your mandate is to build the AI and ML systems that make these datasets manageable and ready for detailed analysis. This role suits someone who thinks like a scientist, builds like an engineer, and communicates like a clinician.   Apply today!

AI & Machine Learning for Translational Discovery Develop and deploy agentic AI applications that enable natural language interaction with clinical data Ground AI outputs in validated biological knowledge, for example implementing RAG pipelines anchored in biomedical ontologies (HPO, Gene Ontology, MeSH, DrugBank), clinical trial registries, and curated pathway databases Deploy unsupervised and self-supervised learning approaches like clustering, representation learning, contrastive learning to discover latent patient archetypes and molecular disease subtypes across trial and biobank data Deploy survival models and dynamic treatment regime estimators using combined clinical and omics features AI tooling to harmonize heterogeneous trial and biobank datasets to common data representations Evaluate and monitor model performance, safety, and reliability in production environments Manage vendors and contractors as well as partner relationships with relevant teams across Lilly   Post-Trial Data Research & Analysis Building pipelines for locked clinical trial databases (SDTM, ADaM) to conduct secondary and exploratory research beyond primary endpoints Deploy ML workflows to identify trial subgroup effects, treatment heterogeneity, and responder/non-responder signatures from completed trial data Mine adverse event narratives, clinical notes, and investigator comments using NLP to surface latent safety signals not