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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Technical Lead - Software Developer, Data Foundry - **Company:** The Lilly Company - **Location:** San Diego, CA, United States - **Experience:** Expert - **Salary:** $151,500.0 - $244,200.0 - **Contract:** Permanent contract - **Skills:** Java (Programming Language), Application Programming Interfaces (APIs), Artificial Intelligence, Airflow, Amazon Web Services, Automation of Tests, Microsoft Azure, Bash Shell, BigQuery, Bioinformatics, C Sharp (Programming Language), Cloud Computing, Code Review, Computational Biology, Databases, Continuous Integration, Custom Software, Data Warehousing, Database Queries, Linux, Experimental Data, Python (Programming Language), Laboratory Information Management Systems, PostgreSQL, Machine Learning, Metadata, Robotic Automation Software, Software Engineering, Software Systems, Data Streaming, TypeScript, Web Platforms, Workflow Management Systems, Delivery Pipeline, Snowflake, Git, Containerization, Kubernetes, Information Technology, Machine Learning Operations, Virtual Agents, Api Design, Software Coding, Restful APIs, Software Version Control, Data Pipelines, Devsecops, Docker, Amazon Redshift, Vulnerability Analysis, Golang, Microservices - **Published:** June 2, 2026 - **Apply:** https://dejobs.org/x/x/4CBF79975C594D618EBD0ACB52556B71/job/ ## About the Role * 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., * 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. ## Description 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. ## Related Videos - [How a Small Team Shrank a Microsoft Monorepo by 94%](https://www.wearedevelopers.com/videos/1236-how-a-small-team-shrank-a-microsoft-monorepo-by-94) - [Docker network without Docker](https://www.wearedevelopers.com/videos/1418-docker-network-without-docker) - [Go with the Flow: Stop the Leaks Before Your Memory's a Waterfall!](https://www.wearedevelopers.com/videos/100073-go-with-the-flow-stop-the-leaks-before-your-memory-s-a-waterfall) - [Geometric deep learning for drug discovery](https://www.wearedevelopers.com/videos/264-geometric-deep-learning-for-drug-discovery) - [Git for Code Reviews](https://www.wearedevelopers.com/videos/429-git-for-code-reviews) - [Data Science, ML & AI in the Oil and Gas Industry at NDT Global - Dr. Katja Träumner](https://www.wearedevelopers.com/videos/1308-data-science-ml-ai-in-the-oil-and-gas-industry-at-ndt-global-dr-katja-traumner) ## Related Articles - [Highest Paying Tech Companies for Developers](https://www.wearedevelopers.com/magazine/220-highest-paying-tech-companies-for-developers) - [How to Become an AI Engineer](https://www.wearedevelopers.com/magazine/331-how-to-become-an-ai-engineer) - [The Most Popular IT Jobs on the Market](https://www.wearedevelopers.com/magazine/376-the-most-popular-it-jobs-on-the-market) - [MLOps And AI Driven Development](https://www.wearedevelopers.com/magazine/82-mlops-and-ai-driven-development) - [Coffee with Developers - Maria Apazoglou - Making AI understandable for all in production](https://www.wearedevelopers.com/magazine/475-coffee-with-developers-maria-apazoglou-making-ai-understandable-for-all-in-production) - [Software Engineer Salary London](https://www.wearedevelopers.com/magazine/252-software-engineer-salary-london)