Technical Lead - Software Developer, Data Foundry

BioSpace; San Francisco (CA); On-site; USD 152,000 - 244,000; Full time

Benefits offered by this job

401(k) plan

Medical, dental, vision benefits

Pension

Vacation benefits

Flexible benefits

Life insurance

Employee clubs

Job summary

Lilly is seeking a Scientific Software Developer to build software powering AI-native drug discovery. You will work directly with discovery scientists to translate needs into prototypes, data pipelines, APIs, ML tooling, and lab automation integrations across Architecture4Insight, Methods4Insight, and Automation & Scale4Insight.

This role centers on rapid prototyping, cloud-native infrastructure, and handoffs to Tech@Lilly for enterprise scaling.

Qualifications

• BS/MS/PhD in CS/biomedical fields with 5+ years of software work.
• Strong Python and SQL skills; experience in APIs and data pipelines.
• Experience building RESTful APIs, microservices or related infra.
• Experience in pharma/biotech discovery workflows is a plus.

Responsibilities

• Design, build, and maintain data pipelines for complex datasets, ensuring FAIR data.
• Develop RESTful APIs and microservices for LIMS, ELNs, instruments, and data warehouses.
• Operationalize cheminformatics and AI/ML models as production APIs.
• Integrate lab automation systems with digital platforms and Data Foundry infra.
• Prototype dashboards/tools for scientists and hand off to Tech@Lilly for scaling.

Skills

Python

SQL

RESTful APIs

Data pipelines

ML/AI tooling

Cloud platforms

Docker/Kubernetes

LIMS/ELN

CI/CD

Cheminformatics

Education

B.S./M.S./PhD in Computer Science, Bioinformatics, Computational Biology, Cheminformatics, Chemistry, Biology, Biomedical Engineering, or related STEM field

Tools

RDKit

Schrödinger

MOE

PostgreSQL

Redshift

Snowflake

BigQuery

Benchling

Docker

Kubernetes

Prefect

Airflow

Nextflow

Job description

At Lilly, the work is demanding because patients are waiting. We unite caring with discovery to help make life better for people around the world, knowing that every decision, every detail, and every day matters. Headquartered in Indianapolis, Indiana, our over 50,000 employees around the globe take on complex challenges to discover and deliver life-changing medicines, strengthen how health is understood and managed, and support the communities we serve. This is hard, urgent, selfless work—but it’s work worth doing. If you’re driven by purpose and ready to bring your best to work that truly matters for patients, we invite you to join us.

Location:

San Francisco, CA

Overview

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.

Position Summary

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.

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.

Basic 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.

Preferred Qualifications

• 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.
• 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.

Lilly is dedicated to helping individuals with disabilities to actively engage in the workforce, ensuring equal opportunities when vying for positions. If you require accommodation to submit a resume for a position at Lilly, please complete the accommodation request form (https://careers.lilly.com/us/en/workplace-accommodation) for further assistance. Please note this is for individuals to request an accommodation as part of the application process and any other correspondence will not receive a response.

Lilly is proud to be an 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.

Our employee resource groups (ERGs) offer strong support networks for their members and are open to all employees. Our current groups include: Africa, Middle East, Central Asia (AMECA), Black Employees at Lilly (BE@Lilly), Chinese Culture Network (CCN), EnAble, Evolve, Lilly Indian Network (LIN), Organization of Latinx at Lilly (OLA), Pride (LGBTQ+ Allies), Veterans Leadership Network (VLN) and Women’s Initiative for Leading at Lilly (WILL).

Actual compensation will depend on a candidate’s education, experience, skills, and geographic location. The anticipated wage for this position is $151,500 - $244,200

Full-time equivalent employees also will be eligible for a company bonus (depending, in part, on company and individual performance).

Benefits

• eligibility to participate in a company-sponsored 401(k)
• pension
• vacation benefits
• eligibility for 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)

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