Technical Lead - Software Developer, Data Foundry

Eli Lilly and Company; San Francisco (CA); On-site; USD 151,500 - 244,200; Full time

Benefits offered by this job

401(k) plan

Company bonus

Comprehensive health benefits

Job summary

Eli Lilly and Company is seeking a Scientific Software Developer to advance AI-native drug discovery. You will design and develop software systems to enhance scientific workflows, focusing on data processing pipelines and integrations with various scientific tools and platforms.

This role involves working directly with scientists, building robust APIs and ML deployment pipelines, and implementing effective cloud solutions. An educational background in a STEM field, along with proficiency in programming languages like Python, is essential.

Qualifications

• Minimum 5 years of experience in scientific software development (PhD), or 10+ years if BS.
• Experience in building data pipelines and microservices for scientific applications.
• Experience with MLOps tooling and cloud platforms.

Responsibilities

• Design and maintain data processing pipelines for complex datasets.
• Develop APIs and microservices for LIMS and data access.
• Build ML deployment pipelines for effective model management.

Skills

Proficiency in Python

Strong SQL skills

Experience building RESTful APIs

Understanding of experimental data types

Education

B.S./M.S./PhD. in Computer Science or related field

Tools

AWS

Docker

Kubernetes

Job description

Lilly is seeking a Scientific Software Developer to build software systems that power AI-native drug discovery.

Location: San Diego, CA; San Francisco, CA; Boston, MA; Louisville, CO; Indianapolis, IN

Responsibilities

Scientific Data Pipelines, APIs & LIMS

• 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.

MLOps & Model Operationalization

• 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.

Agentic Platforms & AI Agent Infrastructure

• 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.

Automation Software & Lab Integration

• 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.

Scientific Prototyping & Tech@Lilly Handoff

• 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.

Cloud Infrastructure & DevSecOps

• 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.

Qualifications

• B.S./M.S./PhD. in Computer Science, Bioinformatics, Computational Biology, Cheminformatics, Chemistry, Biology, Biomedical Engineering, or related STEM field.
• Broad experience: BS (10+ years), MS (5+ years) or PhD (1+ year) in scientific software development 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.

Preferred Qualifications

• Pharmaceutical or biotech research industry experience, especially in discovery workflows for biology, chemistry, biochemistry or automation.
• Experience with 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.

Compensation & Benefits

Salary range: $151,500 – $244,200 annually. This is a full‑time position and employees are eligible for a company bonus, 401(k) plan, pension, vacation, medical, dental, vision, prescription drug, flexible benefits, life and death insurance, and various well‑being resources.

EEO Statement

Lilly is a proud EEO employer and does not discriminate on the basis of age, race, color, religion, gender identity, sex, gender expression, sexual orientation, genetic information, ancestry, national origin, protected veteran status, disability, or any other legally protected status.

Accommodation

If you require accommodation to submit a résumé, complete the accommodation request form. For assistance, please contact Lilly’s disability inclusion team.