Advisor – Software Engineering, Evidence Intelligence

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.  At Lilly, we believe in the extraordinary power of uniting care with discovery to make life better for people around the world. As a global healthcare leader headquartered in Indianapolis, we are driven by a deep sense of purpose—one that reaches far beyond our walls. Every day, our people bring passion, curiosity, and unwavering dedication to their work- discovering and delivering life-changing medicines, advancing the understanding of disease, and extending compassion into our communities through meaningful service and philanthropy. We're looking for individuals who share this purpose—who are inspired to make a lasting difference, and who are ready to help shape a better future for patients across the globe. About Lilly Evidence Intelligence Lilly Evidence Intelligence is a new function that delivers non-promotional and validated Lilly clinical evidence directly to the AI platforms healthcare providers increasingly rely on. The goal is to ensure that the responses healthcare providers receive reflect the most current, verified evidence available, at the speed clinical practice requires.

Overview: Lilly is seeking an Advisor, Software Engineering in Evidence Intelligence to build and maintain the technical infrastructure that delivers Lilly's clinical evidence to Frontier AI platforms — converting evidence into platform-ready formats and enforcing the technical standards that keep the evidence corpus current and trustworthy.  How You Will Succeed Build and maintain ingestion pipelines that parse Lilly clinical evidence into structured formats for large language model retrieval. Design, build and maintain the API and storage layer that stores Lilly clinical evidence and serves it through pre-defined structured requests Configure and maintain the  server and tool-call integrations that connect this infrastructure to partner AI platforms. Implement authentication, per-partner access controls, and audit logging across the delivery surfaces. Monitor pipeline and platform health, and resolve data integrity, latency or availability issues affecting the evidence feed to AI platforms. Collaborate with cross-functional teams, including scientists, researchers, and business stakeholders Basic Qualifications: Bachelor's degree in computer science, software engineering, or a related technical field. 5 years of professional software engineering experience 3 years building and operating cloud-based data infrastructure. Additional Skills/Preferences: Masters degree in computer science, software engineering or a related technical field Experience building tool-calling or connector integrations between backend infrastructure and LLM platforms, such as Model Context Protocol servers, function calling, or plugin frameworks. Proficiency in programming languages such Python and SQL Hands-on experience building and maintaining data pipelines, including ingestion, transformation, and structured output. Experience designing and building APIs (REST or equivalent) that serve structured data at scale. Hands-on experience implementing a Model Context Protocol server. Experience implementing retrieval-augmented generation (RAG) pipelines or working within LLM-adjacent technical frameworks. Experience with JavaScript or TypeScript and modern web frameworks. Experience working in life sciences or