Trial Library

Healthcare

StaffEngineer,Backend&Data

$168–230k San Francisco, California, United States FULL TIME Remote Friendly
Market Sentiment
HIGH DEMAND

Neural analysis suggests this role is
optimal for Senior candidates.

The Brief

“Staff Engineer, Backend & Data at Trial Library”

Industry & Context.

Healthcare
Full Job Description

## Description Trial Library is an AI-native research platform with a mission to improve healthcare outcomes by expanding access to precision medicine.  About Trial Library   Trial Library is an AI-native enrollment and care navigation platform that accelerates access to precision medicine. In collaboration with biopharmaceutical manufacturers, payers, and health systems, Trial Library enables the delivery of clinical trials as a standard care option - improving patient access, advancing oncology outcomes, and reducing the total cost of care. Backed by leading healthcare venture capital firms, Trial Library’s platform is currently deployed in 840+ clinics and 3,000+ providers nationwide. ## About the Role We're hiring a second Staff Engineer to own key parts of our backend and data platform. Our platform supports our teams that identify eligible patients for clinical trials and navigate patients around any barriers to enrolling in a trial. You will take technical leadership of our most critical systems as we navigate a massive architectural shift that will be a step-change in our ability to refer patients to trials: moving from narrow, human-assisted data pulls to robust, automated integrations with EMR systems to ingest complete patient records. If cloud-native architecture, building AI agents to empower our human experts, exploring non-deterministic approaches to patient-trial matching, and handling HIPAA-grade data sounds like the right problem space, please keep reading. Our engineering culture values direct communication, strong ownership, and low-ego collaboration. We laugh a lot and use a ton of Slack emojis. We make decisions quickly, give open feedback, and we have a strong bias toward action. ## How We Build with AI Our use of AI in our products is intended to make our authentic interactions with patients, doctors, and others as meaningful as possible. That means using AI to help with all of the operational aspects of the interactions, from helping decide

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