Sr. Software Engineer (Health AI and Machine Learning)

Scorpion Therapeutics; Palo Alto (CA); Hybrid; USD 180,000 - 240,000; Full time

Benefits offered by this job

Hybrid work model

Job summary

Scorpion Therapeutics is seeking a Senior Software Engineer focused on developing AI systems that leverage genetic datasets to generate personalized health insights. You will design and operate agentic AI pipelines, implement RAG architectures using vector stores, and build evaluation frameworks for model quality.

Responsibilities include ensuring reliable CI/CD deployment, troubleshooting production incidents, and integrating AI into workflows.

Qualifications

• B.S. in Computer Science or equivalent required.
• 4+ years industry experience mandatory.
• Proficiency in Python, PyTorch, Terraform on AWS, Docker, and CI/CD tools.
• Hands-on experience with LLM-powered pipelines, RAG architectures, and vector stores.
• Strong understanding of AI evaluation for health applications.

Responsibilities

• Design and operate agentic AI pipelines.
• Implement Retrieval-Augmented Generation (RAG) architectures using vector stores.
• Build evaluation frameworks for model quality.
• Ensure reliable CI/CD deployment.
• Troubleshoot production incidents.
• Integrate AI into workflows.

Skills

AI system design

Model evaluation

Cross-functional collaboration

Education

B.S. in Computer Science or equivalent

Tools

Python

PyTorch

Terraform on AWS

Docker

CI/CD

Vector stores

LLM pipelines

RAG architectures

Job description

Role: Senior Software Engineer focused on developing AI systems that leverage genetic datasets to generate personalized health insights.

Responsibilities: design and operate agentic AI pipelines, implement Retrieval-Augmented Generation (RAG) architectures using vector stores, build evaluation frameworks for model quality, ensure reliable CI/CD deployment, troubleshoot production incidents, and integrate AI into workflows.

Qualifications: B.S. in Computer Science or equivalent, 4+ years industry experience; proficiency in Python, PyTorch, infrastructure as code (Terraform on AWS), Docker, and CI/CD tools; hands-on experience with LLM-powered pipelines, RAG architectures, and vector stores; strong understanding of AI evaluation for health applications.

Preferred: experience in production AI systems, scientific libraries, and cross-functional collaboration.

High-Value: AI for genetic health insights, scalable production systems, hybrid work model in San Francisco Bay Area, hybrid work setup.