Eli Lilly is looking to develop and deploy transformative AI solutions across its global enterprise to enhance safety, quality, and operational efficiency in areas such as drug discovery, manufacturing, Legal, HR, and Finance.
Requirements
- 2+ years architecting and deploying production AI systems
- Proven success delivering AI solutions in regulated or enterprise wide environments
- Demonstrated experience building production applications with AI-powered development tools (GitHub Copilot, Cursor, Claude, ChatGPT, Grok)
- Hands-on experience designing and deploying autonomous agent systems, including orchestration patterns, tool selection, and failure handling
- Expertise with Model Context Protocols, API integrations, and building extensible AI architectures
- Proficiency in Python, LangChain/LangGraph, vector databases (Pinecone, Weaviate, ChromaDB), embedding models, and advanced prompt engineering
- End-to-end MLOps implementation (model versioning, monitoring, CI/CD for ML)
Responsibilities
- Architect Production AI Systems*: Design and ship scalable autonomous agent platforms that solve real problems—think multi-agent orchestration, not demos. Own the full stack from LLM integration to production deployment.
- Build on Lilly Cortex*: Leverage Lilly's enterprise AI platform to architect sophisticated agentic systems using Model Context Protocol (MCP) for tool integration, Agent-to-Agent (A2A) communication for multi-agent coordination, and dynamic UI frameworks that wrap intelligent experiences around agent workflows. Ship context-aware applications that feel native, not bolted-on.
- Ship Fast with AI Tooling*: Be a power user of AI-assisted development. Use AI development tools like GitHub Copilot, and LLM-driven workflows to 10x your output. Set the standard for how modern engineering teams build with AI.
- Define the AI Platform Strategy*: Own the technical vision for Studio as the company's AI business platform. Make architectural decisions that scale from prototype to enterprise.
- Level Up the Team*: Mentor engineers on modern AI/ML practices, prompt engineering, and agentic patterns. Build a high-trust, high-velocity culture where shipping matters.
- Establish Engineering Standards*: Create the playbook—CI/CD for AI systems, evaluation frameworks, observability for agent workflows, and compliance patterns for regulated environments. Balance innovation with reliability.
- Drive Product Impact*: Partner with product, operations, and business teams to identify high-leverage AI opportunities. Ship features that move metrics, not science projects.
Other
- Bachelor', Masters or PhD degree in Computer Science, Engineering, or related field
- 8+ years of software engineering experience
- Experience leading technical teams through AI transformation initiatives
- Ability to communicate complex technical concepts to diverse audiences—from engineering deep-dives to executive strategy sessions
- Track record of mentoring engineers and fostering innovation within teams
