Scientific Lead - Forward Deployed AI Engineer, Applied Intelligence for Discovery

Lilly is seeking an AI engineer to serve as the connective tissue between what AI can do and what discovery scientists need it to do. This role embeds engineers directly with research teams to translate scientific challenges into production AI systems that accelerate drug discovery workflows.

Key Responsibilities

• Embed with computational biology teams to understand workflows, data constraints, and bottlenecks
• Develop working prototypes with clear success metrics and evaluation benchmarks
• Design and deploy production systems for drug discovery applications
• Apply LLMs, RAG, text-to-SQL, and agentic AI frameworks to target identification and biomarker analysis
• Conduct evaluation loops measuring system quality against scientific benchmarks
• Distill learnings into reusable reference architectures and validation templates
• Partner with AI/LLMOps engineers to feed field solutions back into platform components

Required Qualifications

• PhD in computational biology, bioinformatics, data science, or computer science with 3+ years of software/ML engineering experience; OR
• Master's degree in related field with 5+ years of deployment experience

Technical Skills

• Strong Python programming and modern AI/ML ecosystem familiarity
• LLM experience (API usage, prompt engineering, fine-tuning)
• Frameworks: PyTorch, HuggingFace, LangChain, or LlamaIndex
• Multi-omics data experience (RNA-seq, proteomics, GWAS, spatial transcriptomics preferred)
• AWS and Git proficiency
• Data-driven application development (dashboards, natural language interfaces)

Preferred Qualifications

• End-to-end AI deployment ownership from scoping to production
• Biological foundation model experience (AlphaFold, ESM, Geneformer)
• Knowledge graph and biomedical ontology familiarity
• Track record driving non-technical user adoption