Valar Labs makes diagnostics that use AI to interpret solid tumors and deliver insights, so physicians and patients can make informed treatment decisions. Backed by a16z and Pear VC.
About the role
Build agentic AI pipelines that automate clinical and operational workflows Design the evals and guardrails that make agent driven work trustworthy in a clinical setting
What they're looking for
- Bachelor’s degree in Computer Science or equivalent practical experience
- Strong full stack fundamentals in JavaScript, React and Node
- Experience with Docker, AWS and production deployments
- Daily fluency with agentic coding tools such as Claude Code and Codex, and judgment about where they help
- 2+ years of software engineering experience, exceptional new grads welcome
- (Optional) Experience building LLM powered products or working in healthcare
More about this role
Valar Labs is a well funded, fast-growing AI diagnostics startup backed by leading VCs revolutionizing oncology and urology through cutting-edge technology and innovation. We are dedicated to improving patient outcomes through the development and deployment of novel AI-driven diagnostics to reduce treatment uncertainty for oncologists and patients. Our team comprises accomplished researchers, and passionate individuals committed to shaping the future of healthcare.
Software Engineers at Valar Labs build and run the products that put clinical grade AI in front of oncologists worldwide, and the agentic systems behind them.
Build agentic AI pipelines that automate clinical and operational workflows
Design the evals and guardrails that make agent driven work trustworthy in a clinical setting
Build our clinician facing portal used daily by oncologists, pathologists and care teams
Develop and optimize production environments running AI models to serve thousands of patients
Ship full stack features in a fast-paced daily cadence from prototype to production in a HIPAA environment
Bachelor’s degree in Computer Science or equivalent practical experience.
Strong full stack fundamentals in...
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