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.
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 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 |
|---|---|---|
| Advisor - Agent Research Seeking a scientist-engineer hybrid to deploy AI-driven discovery platforms using foundation models, multi-agent systems, and robotics in drug discovery workflows. The role involves translating scientific workflows into agentic systems, integrating LLM reasoning with domain tools, and supporting model deployment and inference services. | AgentServe | 9 |
| Director, Discovery Bioinformatics Oncology Lead the AI/ML innovation & deployment for oncology discovery, architecting and operationalizing state-of-the-art machine learning (deep learning, foundation models, LLM-powered applications) to accelerate target identification, protein/antibody design, and multimodal data integration. Develop next-gen data integration platforms, advance computational protein & antibody design using active learning, and design/oversee experiments. Deliver robust, scalable ML systems with MLOps on cloud platforms and foundational bioinformatics. |
| AgentData |
| 8 |
| Applied AI Engineer, Clinical Informatics This role focuses on building agentic AI applications and ML systems to extract, define, and contextualize patient phenotypes from clinical trial datasets, biobank data, and electronic health records. It involves developing RAG pipelines, applying unsupervised/self-supervised learning, survival models, and NLP techniques to derive translational insights for clinical research. The role requires strong Python/R skills and experience with cloud environments, with a focus on research rigor and reproducibility. | AgentData | 8 |
| Sr. Principal or Engineering Advisor - Agentic Lab Automation Integration This role focuses on engineering the integration between agentic AI and physical lab systems, specifically for automating and accelerating molecule discovery in a healthcare setting. The engineer will build multi-agent systems, design agent workflows that interact with lab automation platforms, and deploy these systems into production environments. The goal is to create autonomous agents that can execute experiments, reduce experimental cycle times, and become integral to lab operations. | Agent | 8 |
| Advisor - AI-Guided Optimization for Biologics This role focuses on building AI-orchestrated pipelines for biotherapeutics discovery, connecting generative design, property prediction, experiment selection, and result interpretation into a semi-autonomous loop with human oversight. It involves designing active learning pipelines for multi-objective optimization and using reinforcement learning to align generative models for desired therapeutic properties. | AgentPost-train | 8 |
| Director, Discovery Bioinformatics Oncology Lead the AI/ML innovation & deployment for oncology discovery, architecting and operationalizing state-of-the-art machine learning models (deep learning, foundation models, LLMs) to accelerate target identification, protein/antibody design, and multimodal data integration. Develop next-gen data integration platforms, advance computational protein & antibody design using active learning, and design/oversee experiments. Deliver robust, scalable ML systems with MLOps on cloud platforms and ensure foundational bioinformatics practices. | AgentData | 8 |
| Scientific Lead - Forward Deployed AI Engineer, Applied Intelligence for Discovery The Forward Deployed AI Engineer will embed with research teams to translate scientific use-cases into production AI systems for drug discovery. This role involves applying LLMs, RAG, and agentic frameworks to solve scientific problems, running evaluation loops, and distilling learnings into reusable components. The engineer will own end-to-end deployments, ensuring reliability and integrating with AI/LLMOps platforms, with a focus on measurable workflow impact and evidence-based feedback loops. | AgentServe | 8 |
| Software Engineer, AI & Clinical Applications Software Engineer role focused on building AI-powered and agentic applications to automate clinical workflows within a regulated healthcare environment. The role involves full-stack development, architecting LLM-integrated tools, and ensuring compliance with industry standards. | Agent | 7 |
| Applied Bioinformatics Engineer, Pipelines & AI This role focuses on building and scaling analytical pipelines for bioinformatics and genomics data, with a significant emphasis on integrating AI-enabled tooling, including LLMs and agentic workflows. The engineer will prototype agentic workflows for automating analytical tasks, build connectors for LLM agents, and identify use cases for AI to improve research speed and quality. The role requires strong software engineering skills and a curiosity for both classical bioinformatics and modern AI. | Agent | 7 |
| Director – Software Product Management, Enterprise AI Orchestration The Director of Software Product Management for Enterprise AI Orchestration at Eli Lilly will define and drive the strategy for deploying, managing, and optimizing AI agents and workflows at an enterprise scale within the pharmaceutical industry. This role involves owning the product roadmap for an enterprise AI orchestration platform, enabling business units to build and manage AI workforces, and ensuring AI investments deliver measurable business value while adhering to compliance requirements. | Agent | 7 |
| Director - Software Product Management - Silicon Valley Hub Product Management Director to lead strategy, development, and execution of AI products and capabilities in the clinical space, focusing on AI-enabled software products in highly regulated environments. The role involves defining and owning product roadmaps for a complex ecosystem supporting clinical and regulatory workflows, partnering with engineering on technical standards for AI systems, and ensuring solutions meet quality, compliance, and trust expectations. | Agent | 7 |
| Director/Senior Director, Analytical Methods (Methods4Insight) Director/Senior Director, Analytical Methods role within Lilly's Data Foundry team, focusing on developing and deploying cutting-edge analytical methods (cheminformatics, computational structural biology, statistical modeling, AI/ML) to accelerate molecule discovery. This role involves translating advanced methods into practical capabilities for both human scientists and autonomous AI agents, collaborating with other Data Foundry pillars and Frontier AI, and establishing best practices for method validation and impact tracking. | Agent | 7 |
| Sr. Staff Software Engineer - AI Chat Senior Staff Software Engineer to own the technical direction and delivery of ChatNow's core platform, which includes the routing engine that matches intent to the right agent, the integration layer that connects a growing ecosystem of AI capabilities, and the experience layer that makes it all feel effortless. The role involves defining the architecture and driving implementation of the conversation routing engine, owning the agent integration layer, building streaming chat interfaces, and integrating LLM capabilities through a model gateway with multi-model routing and fallback. | Agent | 7 |
| Technical Lead - Software Developer, Data Foundry Scientific Software Developer to build software systems for AI-native drug discovery. This role involves creating prototypes, data pipelines, APIs, MLOps infrastructure, agentic platform components, and lab automation integrations. The work spans architecture, methods, and automation, with a focus on a prototype-to-production model, handing off mature solutions to an enterprise scaling team. Responsibilities include building data pipelines for scientific datasets, developing APIs for LIMS and instruments, implementing MLOps for model deployment and observability, developing agent-ready APIs and infrastructure for closed-loop experimentation, integrating lab automation, and building cloud-native components with DevSecOps practices. | AgentServe | 7 |
| Principal Clinical Development AI Engineer Principal Clinical Development AI Engineer at Eli Lilly to design, build, and deploy AI-powered solutions for clinical development workflows, partnering with statisticians and data engineers. The role involves identifying opportunities, building AI tools (including generative and multi-agent systems), establishing trust standards, and communicating results. Requires experience in AI/ML development and building adopted AI tools, with a focus on regulatory compliance and therapeutic area understanding. | Agent | 7 |
| Director, Software Product Management – Discovery Research Platforms Product Management leader to shape strategy and development of custom software platforms for discovery research, focusing on computational drug design and optimization for large molecules. The role involves integrating agentic AI capabilities into research workflows, accelerating design-make-test-learn cycles, and enabling scientists to compose complex computational pipelines through AI-assisted interfaces. Requires partnership with computational biologists, protein engineers, and engineering teams to translate research needs into scalable software platforms. | Agent | 7 |
| Operations Lead, AI Products & Agents Seeking a senior leader to drive the strategy, operations, and scale-up of AI-powered support products and agentic experiences at Lilly. The role focuses initially on conversational AI products (chatbots) across IT, HR, Finance, and external channels, delivered through multiple platforms. Responsibilities include owning the product operations roadmap, building and managing AI agents and human operators, driving cross-functional alignment, and ensuring exceptional user experiences at scale. The role also involves a platform transformation mandate to consolidate disparate chatbot and support experiences into a unified, agentic platform, identifying new AI agent opportunities, and rationalizing the product portfolio. This is a high-impact role for someone who thrives at the intersection of product strategy, technical operations, and AI, navigating ambiguity and driving ownership. | Agent | 7 |
| Advisor - Lab Automation Software Engineer This role focuses on designing and building AI-integrated, closed-loop autonomous discovery ecosystems for biotherapeutics research. It involves orchestrating automated laboratory workflows, implementing ML models for optimization, and creating digital lab infrastructure. The primary output is an agentic system that proposes hypotheses, executes experiments, analyzes results, and iteratively refines designs. | AgentData | 7 |