About Rad AI

At Rad AI, we’re on a mission to transform healthcare with artificial intelligence. Founded by a radiologist, our AI-driven solutions are revolutionizing radiology—saving time, reducing burnout, and improving patient care. With one of the largest proprietary radiology report datasets in the world, our AI has helped uncover hundreds of new cancer diagnoses and reduced error rates in tens of millions of radiology reports by nearly 50%.

Rad AI has secured over $140M in funding, including a recently oversubscribed Series C ($68M round) led by Transformation Capital, bringing our valuation to $528M. Our investors include Khosla Ventures, World Innovation Lab, Gradient Ventures, Cone Health Ventures, and others—all backing our mission to empower physicians with cutting-edge AI.

Our latest advancements in generative AI are used by thousands of radiologists daily, supporting more than one-third of radiology groups and healthcare systems and nearly 50% of all medical imaging in the U.S. at partners including Cone Health, Jefferson Einstein Health, Geisinger, Guthrie Healthcare System, and Henry Ford Health.

Recognized as one of the most promising healthcare AI companies by CB Insights and AuntMinnie, and ranked by Deloitte as the 19th fastest-growing company in North America, we are building AI-powered solutions that make a real impact. Most recently, Rad AI was named to CNBC’s Disruptor 50 list, highlighting the innovation and momentum behind our mission.

If you’re ready to shape the future of healthcare, we’d love to have you on our team!

Why Join Us

We're adding a Senior Technical Support Engineer to our Technical Support team during the fastest period of customer growth in Rad AI's history. You'll be the technical escalation point for a portfolio of enterprise health systems and radiology groups, own our most complex Reporting, Impressions and integration issues end to end, and help shape how a scaling support function runs: process, tooling, automation, and the next generation of TSEs.

What You'll Be Doing

Serve as the senior technical escalation point for complex, multi-system issues spanning our Reporting platform, HL7/integration layer (Interlinx, Medplum), speech recognition, and customer Windows/PACS environments, driving them to root cause rather than workaround.

Own high-visibility customer incidents: lead the TS response during P1/P2 events, coordinate with Engineering on-call, run customer-facing bridges, and deliver post-incident reviews and RCAs on time.

Lead technical support coverage for enterprise go-lives, including readiness reviews with Implementations, hypercare, and the handoff into steady-state support.

Drive ticket quality and SLA attainment across the team through triage standards, escalation criteria, and Zendesk/Linear workflow design; identify volume drivers and work with Product and Engineering to eliminate them.

Build and maintain runbooks, troubleshooting guides and Help Center content for new products and integrations; raise the technical floor of the team through mentoring, shadowing and ticket reviews.

Partner with our automation and AI workstream to design, test and roll out triage, classification and self-service tooling that reduces manual ticket handling.

Represent Technical Support in Engineering triage, incident review and release planning, bringing customer impact data to prioritization decisions.

Participate in and help lead the on-call rotation, including occasional night/weekend coverage, and contribute to the design of 24/7 coverage as the team scales.

Who We're Looking For

You will be working west coast (PST) overnight hours (12am - 10am PST)

This overnight support role works Wednesday through Saturday, providing overnight coverage for customers, including weekends.

6+ years in customer-facing technical roles (support engineering, TAM, solutions/implementation engineering) supporting enterprise SaaS, with at least 2 years operating as a senior or lead escalation resource.

Healthcare IT depth: hands-on experience with HL7 v2 messaging (ORU/ORM/ADT), interface engines, and PACS/RIS or dictation workflows in a radiology or hospital setting.