Software Engineer, Oncology Applications
About The Position
The Software Engineer, Oncology Applications designs, builds, integrates, and sustains applications that connect people, data, systems, and workflows across Oncology research and business operations. The role serves the Oncology organization broadly and partners with discovery and translational teams, scientific platforms, informatics, research operations, and Tech@Lilly. Work may include scientific data applications, workflow and process tools, dashboards and reporting, system integrations, automation, and AI-enabled interfaces. The application portfolio will evolve with Oncology priorities and technologies. The engineer is expected to apply sound engineering practices, use AI-assisted development thoughtfully, and focus on secure, tested, maintainable systems. The position is primarily computational and office-based, with regular in-person collaboration with laboratory, informatics, technology, and operations teams. Travel is less than 5%.
Requirements
- BS or MS in computer science, software engineering, or a related discipline, with 4 or more years of professional software engineering experience; an equivalent combination of education and demonstrated experience will be considered.
- Strong programming experience with Python or another modern server-side language; Python is preferred.
- Experience developing web applications or APIs using modern server-side frameworks; preferred frameworks include Django, Flask, and Ruby on Rails.
- Front-end development experience with JavaScript or TypeScript and a modern component framework.
- Experience with relational database design, SQL, APIs, and system integration.
- Experience with cloud deployment, preferably AWS, as well as containerization and CI/CD pipelines.
- Fluency with Git-based collaborative development, code review, automated testing, and production support.
- Experience with AI-assisted development tools and working familiarity with LLM APIs or related application patterns.
- Ability to work directly with scientific and operational stakeholders and communicate technical options clearly to non-engineers.
- Demonstrated ability to work independently, manage concurrent projects, and adapt to changing priorities.
Nice To Haves
- Experience developing scientific, operational, or data-intensive business applications.
- Prior work in pharma, biotech, healthcare, research, or another regulated environment.
- Experience with biological data, laboratory systems, scientific instruments, or research data pipelines.
- Experience with workflow automation, enterprise integration, reporting, or interactive data visualization.
- Experience developing AI-enabled or agentic applications over internal data sources.
- Familiarity with data governance, sensitive-data handling, or controlled-access systems.
Responsibilities
- Design, build, deploy, and sustain full-stack applications, data services, workflow tools, and automation for scientific and operational users.
- Partner with scientists, engineers, informatics teams, and business stakeholders to identify needs, clarify requirements, and define practical deliverables.
- Improve efficiency by simplifying processes, reducing manual handoffs and duplicative data entry, and connecting fragmented data and systems.
- Build and maintain APIs, data models, and access layers across scientific, operational, enterprise, and vendor data sources.
- Integrate applications with laboratory systems, data pipelines, analysis environments, and enterprise platforms.
- Apply appropriate standards for data quality, provenance, versioning, security, and access control.
- Develop AI-enabled capabilities where they provide clear value, such as information retrieval, natural-language data access, extraction, annotation, and summarization.
- Use AI-assisted development tools while maintaining established standards for code review, testing, security, and ownership.
- Evaluate technology options and recommend whether needs are best addressed through custom development, configuration, integration, reuse, purchase, process change, or retirement.
- Contribute to shared engineering practices, including version control, peer review, automated testing, CI/CD, containerization, observability, and dependency management.
- Deploy and operate applications on Lilly cloud infrastructure in partnership with Tech@Lilly and Information Security.
- Own application reliability, user support, documentation, maintenance, and lifecycle planning.
- Mentor junior engineers, co-ops, and scientist-developers as appropriate.
Benefits
- Company bonus, depending in part on company and individual performance.
- Eligibility to participate in a company-sponsored 401(k).
- Pension.
- Vacation benefits.
- Eligibility for medical, dental, vision, and prescription drug benefits.
- Flexible benefits, such as 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, including an employee assistance program, fitness benefits, and employee clubs and activities.
- Employee resource groups offering support networks and open to all employees.
Stand Out From the Crowd
Upload your resume and get instant feedback on how well it matches this job.
What This Job Offers
Job Type
Full-time
Career Level
Mid Level
