Eli Lilly

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.

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.

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.