4 hours ago
Base Salary
$165k - $200k/yr
Responsibilities
- Build agentic AI systems that generate personalized health and ancestry insights by orchestrating LLMs with genetic and clinical context.
- Design and implement RAG pipelines that retrieve context from vector stores and ground model outputs in customer genetic data.
- Build evaluation frameworks to measure model quality, detect regressions, and validate health-product results.
- Use CI/CD methods and automated testing to deliver reliable code continuously.
- Debug production incidents, restore services, and own shipped systems.
- Integrate AI into daily workflows to automate tasks and improve organizational efficiency.
Requirements
- B.S. in Computer Science or equivalent and 4+ years of industry experience.
- Hands-on production experience building agentic AI systems and LLM-powered pipelines.
- Experience with RAG architectures and vector stores.
- Strong understanding of LLM evaluation and quality measurement for health products.
- Proficiency with Python and scientific libraries including pandas and PyTorch.
- Infrastructure-as-code experience, ideally with Terraform on AWS, and containerization with Docker.
- Hands-on experience with CI/CD deployment pipelines and testing frameworks.
- Ability to work cross-functionally as a team player.
Benefits
- Hybrid work model based in the San Francisco Bay Area, California.
- Small, high-trust team offering ownership, autonomy, and direct impact on a scientifically rich genetic dataset.
- Opportunity to work with R&D and bioinformatics teams at the intersection of software engineering and genetic research.
- AI-friendly team that uses tools such as Claude Code.
- Direct impact through systems serving millions of people and frequent shipments multiple times per week.
