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 development tools and workflows to improve engineering productivity, while maintaining high standards for code quality, reliability, and security.
Nice to Haves:
Experience with PostgreSQL
Experience with 3rd-party integrations such as Auth0, Amplitude
Experience working at an early-stage startup
Experience in a HIPAA-compliant environment, especially with FHIR and HL7
Experience working on machine learning
Join our world-class team as we build and deploy AI solutions that empower physicians and transform patient care-making a meaningful impact on millions of lives. Driven by our mission, we prioritize transparency, inclusion, and close collaboration, bringing together exceptional people to revolutionize healthcare. If you're passionate about driving innovation and delivering impactful healthcare solutions, we'd love to hear from you!
To learn more about what it's like to work at Rad AI, visit https://www.radai.com/life-at-rad-ai and be sure to follow us on LinkedIn to stay up to date!
Location Details:
For roles listed as San Francisco - Onsite:
This role will be based in our San Francisco office and we expect employees to work onsite four days per week. The remaining time may be worked remotely or onsite, depending on team and business needs.
For roles listed as United States - Remote:
This role is open to candidates located anywhere in the United States.
For roles listed as San Francisco - Onsite + United States - Remote:
We will prioritize candidates who can work onsite four days per week in San Francisco, while also considering remote candidates located anywhere in the United States.
For US-Based Full-Time Roles, Rad AI offers a variety of benefits, including:
Comprehensive Medical, Dental, Vision & Life insurance
HSA (with employer match), FSA, & DCFSA
401(k)
11 Paid Company Holidays
Flexible PTO policy
Annual company-wide offsite
Periodic team offsites
Annual equipment stipend
For roles based outside the US, your recruiter can share more details
At Rad AI, we value diversity and provide equal employment opportunities (EEO) to all employees and applicants without regard to race, color, religion, national origin, gender, sexual orientation, age, marital status, veteran status, or disability status. We will consider for employment qualified applicants with criminal histories in a manner consistent with the requirements of the San Francisco Fair Chance Ordinance.
Please be vigilant regarding job scams. We advise all candidates to apply directly through our official careers page. Our recruiters will use email addresses with the domain @ radai.com or [email protected].