Technical Lead - Software Developer, Data Foundry
Eli Lilly and Company · Boston, MA · 1 mo ago
Engineering$152k–$244k/yrFull-time
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.
- Create integrations connecting lab automation equipment, scheduling systems, and instrument data streams to Data Foundry’s infrastructure with proper metadata and traceability.
- Build 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.
Requirements
- B.S./M.S/Phd. in Computer Science, Bioinformatics, Computational Biology, Cheminformatics, Chemistry, Biology, Biomedical Engineering, or related STEM field.
- B (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.