Eli Lilly

Research Advisor/Sr. Advisor role focused on applying and developing innovative AI/ML models for drug discovery, specifically in ADMET Intelligence. The role involves integrating AI/ML with Chemistry and Biology, developing scientific foundation models, and collaborating with experimental scientists. The goal is to advance drug discovery by connecting computational predictions with lab experiments and publishing research findings.

Research Scientist role focused on designing, implementing, and evaluating deep learning architectures (transformers, diffusion models, GNNs) for protein design and engineering in drug discovery. The role involves multi-modal representation learning, cross-modality molecular modeling, and physics-informed training objectives, collaborating with computational biology and IT teams.

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.

Senior Principal Software Engineer to own architecture, design, and delivery of complex software systems, championing AI and agentic engineering practices. Responsibilities include system design, hands-on coding, building RAG pipelines and agentic systems, evaluating foundation models, and technical leadership.

Associate Director of AI Engineering at Eli Lilly, responsible for leading a team to build and operationalize production-grade AI systems, including traditional ML and agentic AI (LLM/agent workflows, tool use, orchestration). Focus on establishing best practices, building reusable capabilities, implementing observability, and ensuring secure, compliant AI delivery in a regulated healthcare environment.

The role focuses on defining and implementing the technical architecture strategy for AI solutions within the Lilly Medicine Foundry. This includes designing foundational platforms, standards, and architectural patterns for AI/ML systems, MLOps infrastructure, model lifecycle management, and generative AI capabilities like RAG and agentic systems. The role also emphasizes technical standards, governance, and compliance within the pharmaceutical industry context.

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.

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.

Associate Vice President of Applied Intelligence for Discovery (AI4D) at Eli Lilly, responsible for the technical vision and execution of AI capabilities to transform drug discovery research. This role involves building and leading a multidisciplinary team, setting the technical roadmap for AI/ML platforms, guiding architecture decisions for end-to-end ML workflows, and driving adoption of MLOps practices. The goal is to create computationally driven discovery processes by building platforms where AI enables new workflows, moving beyond mere computational support.

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.

Advisor Software Engineer (R5) role focused on designing and building agentic AI systems, intelligent automation pipelines, and next-generation software platforms. This is a hands-on technical leadership role involving system design, full-stack engineering, and championing AI-driven development practices within a healthcare company.

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.

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.

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.

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.

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.

Principal Software Engineer to join the AI & Platform team, focusing on designing, building, and scaling intelligent systems using Generative AI and LLMs. The role involves implementing agent-based AI workflows and integrating AI capabilities into production systems, working across backend and frontend components.

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.

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.

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.

Computational Biologist role focused on analyzing multimodal biological datasets (spatial and single-cell omics, proteomics, metabolomics, functional genomics) to advance target discovery in cardiometabolic diseases. The role involves developing predictive models, integrating diverse data types, applying AI/ML and causal inference methods, and influencing data architecture and analytical standards. Collaboration with internal AI and data engineering teams is key.

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.

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.

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.

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.

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.

This role focuses on delivering advanced analytics and predictive modeling for pharmaceutical manufacturing and development processes. The Senior/Principal Data Scientist will build, validate, and maintain statistical models for real-time process monitoring, anomaly detection, and performance optimization. They will collaborate with cross-functional teams, IT, and global stakeholders to deploy secure, scalable analytics solutions, ensuring data integrity and compliance with GMP and regulatory standards. The role involves data integration, visualization, and driving digital transformation within a regulated healthcare environment.

Product Manager for GenAI products at Eli Lilly, focusing on defining vision, strategy, and execution. Requires experience with GenAI concepts, agent evaluation, and AI tools, bridging user needs with technical delivery in a healthcare context.

Principal Engineer - Quality Engineering role focused on designing and building evaluation frameworks for AI platforms (LLM chat/voice bots) and robust test automation for API, web, and mobile applications. Requires hands-on Python, Java, JavaScript/TypeScript for test infrastructure, CI/CD integration, and advanced AI testing methodologies. Also involves performance testing and cloud-based execution.

Technical Lead Software Architect for the AI & Platform team at Eli Lilly, focusing on designing, building, and scaling intelligent systems using Generative AI and LLMs. The role involves owning end-to-end delivery of GenAI/LLM platform capabilities, designing multi-agent AI architectures, and establishing engineering best practices for cloud-native solutions. Requires expertise in backend and frontend development, agentic AI frameworks, containerization, and cloud platforms.

Senior Principal Software Engineer to join the AI & Platform team, focusing on designing, building, and scaling intelligent systems using Generative AI and LLMs. The role involves end-to-end delivery of GenAI/LLM-powered platform capabilities, designing multi-agent AI architectures, and working across backend and frontend layers. Requires strong software engineering skills, cloud-native architecture experience, and familiarity with agentic AI frameworks.

This role focuses on developing and implementing a digital strategy for integrating AI, ML, and automation into quantitative pharmacology and pharmacometrics workflows within a healthcare setting. The goal is to accelerate drug development, position the organization as an industry leader in AI-enabled drug development, and ensure scientific rigor and regulatory compliance. The role involves evaluating emerging AI technologies, leading pilots, partnering with IT and data science teams, driving AI adoption through organizational change, and defining success metrics.

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.

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.