Scientific Software Developer, Data Foundry

Scientific Software Developer, Data Foundry

Location:

San Francisco, CA

Lilly Small Molecule Discovery is purpose-built to create molecules that make life better for people. Discovery Technology and Platforms (DTP) accelerates molecule discovery by building optimized foundational platforms, streamlining lab operations through advanced technologies and data connectivity, and investing in novel capabilities. Data Foundry is a multidisciplinary team within DTP that enables AI‑native drug discovery through four integrated pillars:
Architecture4

Insight (data infrastructure and scientific software), Methods4

Insight (analytical and computational methods), Automation & Scale4

Insight (lab automation and agentic workflows), and Preparedness4

Insight (data governance and readiness). These pillars empower every Lilly scientist to make optimal decisions by providing seamless access to data, insights, and AI‑driven capabilities—serving both human scientists and autonomous AI agents.

We are seeking Scientific Software Developers at multiple levels to build the data infrastructure, scientific tools, and lab automation integrations that power AI‑native drug discovery. You will work directly with front‑line discovery scientists and data scientists to translate their needs into fit‑for‑purpose prototypes, data pipelines, APIs, and workflow tools—then hand off mature solutions to Tech@Lilly for enterprise scaling and maintenance if and when needed.

This role is anchored in Architecture4

Insight with close collaboration across Methods4

Insight and Automation & Scale4

Insight. You will build the scientific software that other teams—including the Frontier AI group’s autonomous agents—consume. Some developers will specialize in lab automation software: building the code that interfaces with physical instruments, robotic platforms, and scheduling systems to enable Scale4

Insight’s closed‑loop experimentation.

Design, build, and maintain data processing pipelines for complex scientific datasets (chemical, biological, high‑throughput experiments, and automation‑generated data), ensuring FAIR compliance and machine‑actionability. Develop RESTful APIs and microservices providing unified programmatic access to LIMS, ELNs, instruments, data warehouses (Postgres, Redshift, Snowflake), and analytical databases. Support continuous improvement of LIMS and adjacent systems to meet evolving scientific workflows, security, and scalability standards.

Work directly with bench scientists to understand pain points and rapidly prototype custom applications, dashboards, and workflow tools. Validate prototypes through iterative scientist feedback, ensuring solutions are fit‑for‑purpose before transition. Partner with Tech@Lilly Product Engineering to hand off mature prototypes for enterprise scaling, defining transition criteria, documentation standards, and SLAs.

Build integrations connecting lab automation equipment, scheduling systems, and instrument data streams to Data Foundry’s infrastructure with proper metadata and execution traceability. Develop software for robotic workflow control, instrument driver interfaces, and real‑time data capture from automated platforms. Create modular, reusable automation workflow components scientists can configure without writing code. Support Scale4

Insight’s Agentic Lab by building software enabling seamless interfacing between automation platforms and AI‑driven experimental planning.

Build and operate cloud‑native components (AWS, Azure, or GCP) supporting containerized workflows (Kubernetes/Docker), infrastructure‑as‑code, CI/CD, and workflow orchestration (Prefect, Airflow, Nextflow). Apply Dev Sec Ops  standards including security scanning, code review, and automated testing. Participate in agile development with iterative improvement and cross‑functional collaboration.

• B.S. or M.S. in Computer Science, Bioinformatics, Cheminformatics, Computational Biology, Chemistry, Biology, Biomedical…