Technical Lead - Software Developer, Data Foundry

Eli Lilly and Company • San Diego, CA

3d • Hybrid

About The Position

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: Architecture4Insight (data infrastructure and scientific software), Methods4Insight (analytical and computational methods), Automation & Scale4Insight (lab automation and agentic workflows), and Preparedness4Insight (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 a Scientific Software Developer to build the software systems that power AI-native drug discovery. You will work directly with front-line discovery scientists to translate their needs into fit-for-purpose prototypes, data pipelines, APIs, MLOps infrastructure, agentic platform components, and lab automation integrations. This role works across Architecture4Insight, Methods4Insight, and Automation & Scale4Insight. A defining aspect is Data Foundry’s prototype-to-production operating model: you will rapidly build and validate solutions with scientists, then hand off mature prototypes to Tech@Lilly for enterprise scaling and maintenance—keeping you focused on innovation and the next high-impact problem.

Requirements

• B.S./M.S/Phd. in Computer Science, Bioinformatics, Computational Biology, Cheminformatics, Chemistry, Biology, Biomedical Engineering, or related STEM field.
• BS (with 10+years), MS (with 5+ years) or Phd (1+ year) of scientific software development experience, with understanding of experimental data types and scientific workflows.
• Proficiency in Python and at least one additional language (Java, C#, Go, TypeScript, or Rust); strong SQL skills.
• Experience building RESTful APIs, data pipelines, and/or microservices for scientific or technical applications.

Nice To Haves

• Pharmaceutical or biotech research industry experience, particularly in discovery workflows for biology, chemistry, biochemistry or automation.
• MLOps tooling: experiment tracking (MLflow, W&B), model registries, model serving, monitoring/drift detection.
• Familiarity with cloud platforms (AWS, Azure, or GCP), containerization (Docker/Kubernetes), and Git.
• Strong communication skills with a track record of productive scientist collaboration.
• Exposure to AI agent infrastructure, MCP frameworks, or building APIs that AI/ML systems invoke programmatically.
• Experience integrating lab automation systems with digital platforms or AI-driven workflows.
• Hands-on experience with cheminformatics tools (RDKit, Schrödinger, MOE) or bioinformatics platforms.
• Data warehousing experience (Postgres, Redshift, BigQuery, Snowflake) and scientific data standards/ontologies.
• LIMS/ELN experience (e.g., Benchling) and laboratory instrument integration.
• Workflow orchestration (Prefect, Airflow, Nextflow, WDL), CI/CD, and Linux/bash scripting.
• Strong learning agility—willingness to step outside comfort zone and adopt new technologies to get the job done.

Responsibilities

• Design, build, and maintain data processing pipelines for complex scientific datasets (chemical, biological, HTE, 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.
• Build ML deployment pipelines—experiment tracking, model versioning (MLflow, W&B), containerized serving, monitoring, and automated retraining.
• Implement model observability: drift detection, performance alerting, and lifecycle management.
• Collaborate with Methods4Insight to operationalize cheminformatics, statistical, and AI/ML models as production APIs.
• Develop agent-ready APIs with structured error handling, audit trails, and monitoring supporting agent autonomy and human oversight.
• Contribute to MCP servers or similar frameworks exposing Data Foundry capabilities to AI agents.
• Build software enabling closed-loop experimentation: agents design, automation executes, data flows back, models update.
• Build integrations connecting lab automation equipment, scheduling systems, and instrument data streams to Data Foundry’s infrastructure with proper metadata and traceability.
• Create modular, reusable automation workflow components scientists can configure without writing code.
• Work directly with bench scientists to rapidly prototype custom applications, dashboards, and workflow tools to improve scientist’s experience and efficiency.
• Validate prototypes through iterative scientist feedback, then partner with Tech@Lilly to hand off for enterprise scaling with defined transition criteria and documentation.
• 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 DevSecOps standards including security scanning, code review, and automated testing.

Benefits

• company bonus (depending, in part, on company and individual performance)
• company-sponsored 401(k)
• pension
• vacation benefits
• medical, dental, vision and prescription drug benefits
• flexible benefits (e.g., healthcare and/or dependent day care flexible spending accounts)
• life insurance and death benefits
• certain time off and leave of absence benefits
• well-being benefits (e.g., employee assistance program, fitness benefits, and employee clubs and activities)

What This Job Offers

• Job Type: Full-time
• Career Level: Senior
• Number of Employees: 5,001-10,000 employees