About the role
About Triomics
Triomics is building the agentic AI layer for oncology EHRs. Cancer hospitals spend billions on highly trained staff manually reading unstructured patient records - pathology reports, clinical notes, genomic panels - to power workflows like trial matching, registry curation, visit prep, and quality reporting. We replace that manual work with task-driven AI agents that sit inside the EMR and process records at scale, in real time.
Our platform is trusted by leading cancer centers including Memorial Sloan Kettering, Mount Sinai, and Yale Cancer Center. We have grown 10x in the last year and process millions of oncology medical documents monthly.
Our investors include Battery Ventures, Lightspeed, General Catalyst, Nexus Venture Partners, and Y Combinator.
The Role
We have live deployments at some of the best cancer centers in the world, and multiple products in production at scale.
We are looking for a Director of Engineering to own that. You will run all of product and platform engineering - the application teams behind the platform, infrastructure, and reliability function; and frontend. The engineering leads across these areas will report to you.
You will report to the CTO and take day-to-day ownership of how engineering plans, builds, ships, and operates.Your job is to raise the bar. This is not a hands-off role. You'll set technical direction, sit in design reviews, get into production incidents, and solve problems for strong senior engineers - while building the process, and standards that let a ~20-person team ship like a much larger one.
What You'll Own
All engineering execution. Application engineering, platform and infrastructure, reliability, and frontend. You own what ships, when it ships, and how good it is.
Production reliability and quality. Our customers are clinicians making care and research decisions on our output. Every error erodes trust, and clinical users don't give second chances. Own the observability across multi-tenant deployments, catching pipeline failures and data-quality regressions before customers do, incident response, and a real testing and code-quality culture.
