About the role
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! About the SDK and DICOM Routing DICOM is the standard for moving medical images across the imaging stack—between modalities, PACS, viewing workstations, AI services, and downstream reporting systems. How well that flow is orchestrated determines whether AI can be deployed reliably at scale: which studies get routed where, how outputs come back, and how everything stays in sync with the radiologist's workflow. DICOM routing is the plumbing that makes the rest of the platform possible. The Rad AI SDK is how partners across the imaging ecosystem—AI vendors, modality and PACS providers, reporting and workflow tools, and downstream care systems—plug into that platform. It is the surface where partner-generated content (preliminary reports, findings, measurements, worklist signals, and more) flows into the radiologist's reporting experience, and where partners can consume the routing, orchestration, and reporting capabilities Rad AI exposes. A well-designed SDK turns Rad AI Orchestration from an internal platform into an open ecosystem. Together, DICOM routing and the SDK form the connective layer that makes Rad AI's broader platform real: routing standardizes how images and AI outputs move, and the SDK standardizes how partners build on top of it.
