Staff Software Engineer, Continuity

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 Continuity:

Continuity is Rad AI’s care coordination and follow-up product, helping radiology teams make sure important findings do not fall through the cracks. The team builds and operates the applications, APIs, and integrations that turn clinical data into actionable workflows for customers, with a strong emphasis on reliability, scalability, and operational excellence in a sensitive healthcare environment. This work sits at the intersection of product, engineering, implementations, and customer needs, and is central to helping Rad AI deliver measurable value for health systems and radiology practices.

Why Join Us:

We’re seeking a Staff Software Engineer to join our team building the future of radiology. This role will work alongside our high-performing cross-functional team of Full Stack Engineers, ML Engineers, Product Leaders, and various other teams internally and externally to develop this responsive and performant application.

What You'll Be Doing:

• Develop on large-scale progressive and single page web applications that streamline user workflows and increase their efficiency and effectiveness

• Develop our Python, FastAPI backend services including a REST API and ML pipeline services

• Build new features that support our rapidly growing number of customers

• Write code that meets our internal standards for security, style, maintainability, and best practices for a high-scale HIPAA web environment

• Work with Product Management, ML, Data Science, Customer Success and other stakeholders to iterate on new features and address defects

• Advocate for improvements to product quality, security, and performance that have impact across your team

• Mentor engineers on the team through technical guidance, code reviews, design collaboration, and development of strong engineering practices.

Who We're Looking For:

• 7+ years of industry engineering experience with single and multi-tenanted environments

• In-depth knowledge of Python and FastAPI, or equivalent modern languages/frameworks

• Knowledge of relational and document based databases, as well as other large scale data storage paradigms

• Knowledge of modern web architecture and best practices

• Experience with unit and integration testing

• Experience working on a distributed team and strong version control skills using git

• Experience with performance and optimization problems, particularly at large scale, and a demonstrated ability to diagnose and prevent these problems

• Experience using AI-assisted developmen