Eli Lilly

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.

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.

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.

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.

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.

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.

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.

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.

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 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.

Lead enterprise technology strategy and architecture for a healthcare company, focusing on AI transformation, machine learning, advanced analytics, and automation. This role involves researching industry innovations, driving solutions, shaping architectural vision, and overseeing the functional technology portfolio to enable business outcomes and growth.

Associate Director for BI&A HCP Product Analytics at Eli Lilly, responsible for leading the development and implementation of analytical products, championing AI-ready data, and managing the product lifecycle. The role involves collaborating with data engineering and business partners to drive data-driven decisions and ensure compliance.

Senior Consultant for Consumer Analytics Data Engineering at Eli Lilly, focusing on the Databricks and AWS platforms. The role involves designing and maintaining data pipelines, lakehouse architectures, and semantic layers to support advanced analytics and AI/agentic workflows for consumer insights. Key responsibilities include ETL/ELT pipeline development, Databricks platform management, lakehouse architecture design, AWS data service integration, semantic layer publishing, and building agentic workflows.

This role focuses on integrating software and AI capabilities into laboratory automation for antibody discovery. The engineer will lead the design and implementation of software integrations between automation infrastructure and digital tools, including exploring and prototyping AI-driven decision-making in workflows. The goal is to build intelligent systems for closed-loop autonomous discovery, accelerating biologics development.

This role focuses on developing and executing omnichannel and personalization strategies within the healthcare industry, with a specific emphasis on leveraging AI tools for sales support and business transformation. The position involves strategic planning, data analysis, cross-functional collaboration, and project management to enhance customer experience and drive business impact.