Software Engineer, Oncology Applications

Scorpion Therapeutics; San Francisco (CA); On-site; USD 170,000 - 210,000; Full time

Benefits offered by this job

Company bonus

401(k)

Pension

Vacation

Medical/dental/vision/prescription

Flexible benefits

Life insurance

Well-being

Job summary

Scorpion Therapeutics designs, builds, and sustains oncology software applications to improve access to information, reduce manual work, and help teams operate more efficiently across research and business operations.

You will partner with scientists, engineers, informatics and business stakeholders to deliver scalable full-stack solutions, APIs, data models, and AI-enabled capabilities while adhering to data governance and security standards.

Qualifications

• BS/MS in CS/software engineering (or related) + 5+ years professional software engineering (equivalent education/experience accepted).

Responsibilities

• Design, build, deploy, and sustain full-stack applications, data services, workflow tools, and automation.
• Partner with scientists/engineers/informatics/business stakeholders to identify needs, clarify requirements, and deliver solutions.
• Improve efficiency by simplifying processes, reducing handoffs/duplicative data entry, and connecting fragmented systems.
• Build and maintain APIs, data models, and access layers across scientific/operational/enterprise/vendor sources.
• Integrate with lab systems, data pipelines, analysis environments, and enterprise platforms.
• Apply standards for data quality, provenance, versioning, security, and access control.
• Develop AI-enabled capabilities (e.g., retrieval, natural-language access, extraction/annotation/summarization).
• Use AI-assisted development while meeting code review/testing/security/ownership standards.

Skills

Python

JS/TS

API design

Cloud AWS

CI/CD

Git

AI-assisted

Data pipelines

Regulated env

Communication

Education

BS/MS in CS/Software Eng

Tools

AWS

Docker

Kubernetes

CI/CD tools

LLM APIs

Job description

Position Summary: Design, build, integrate, and sustain oncology software applications that improve access to information, reduce manual work, and help teams operate more efficiently across research and business operations.

Key Responsibilities

• Design, build, deploy, and sustain full-stack applications, data services, workflow tools, and automation.
• Partner with scientists/engineers/informatics/business stakeholders to identify needs, clarify requirements, and deliver solutions.
• Improve efficiency by simplifying processes, reducing handoffs/duplicative data entry, and connecting fragmented systems.
• Build and maintain APIs, data models, and access layers across scientific/operational/enterprise/vendor sources.
• Integrate with lab systems, data pipelines, analysis environments, and enterprise platforms.
• Apply standards for data quality, provenance, versioning, security, and access control.
• Develop AI-enabled capabilities (e.g., retrieval, natural-language access, extraction/annotation/summarization).
• Use AI-assisted development while meeting code review/testing/security/ownership standards.
• Evaluate and recommend build vs. configure/integrate/reuse/purchase/process change/retirement.
• Use shared practices: version control, peer review, automated testing, CI/CD, containerization, observability, dependency management.
• Deploy/operate on cloud in partnership with Tech@Lilly and Information Security; ensure reliability, support, documentation, maintenance, and lifecycle planning.
• Mentor junior engineers/co-ops/scientist-developers as appropriate.

Required Qualifications

• BS/MS in CS/software engineering (or related) + 5+ years professional software engineering (equivalent education/experience accepted).

Preferred Qualifications/Skills

• Python (preferred) or other modern server-side language.
• Web apps/APIs with modern frameworks (Django/Flask/Rails).
• Front-end in JS/TS with component framework.
• Relational DB design/SQL, APIs, integration.
• Cloud (prefer AWS), containers, CI/CD.
• Git, code review, automated testing, production support.
• AI-assisted tools and familiarity with LLM APIs.
• Communicate with non-engineers; work independently and manage concurrent projects.
• Experience with data-intensive/scientific/operational apps; regulated environments; biological data/lab systems/pipelines.
• Workflow automation, enterprise integration, reporting/visualization; AI-enabled/agentic apps; data governance and controlled-access systems.

Benefits (if eligible)

• company bonus (based on performance)
• 401(k)
• pension
• vacation
• medical/dental/vision/prescription
• flexible benefits
• life/death benefits
• time off/leave
• well-being (EAP, fitness, clubs)