Rad AI
Healthcare
StaffSoftwareEngineer,Infrastructure
Neural analysis suggests this role is
optimal for Senior candidates.
“Staff Software Engineer, Infrastructure at Rad AI. Skills: Infrastructure, Platform engineering, Cloud infrastructure, Reliability”
Industry & Context.
Debugging issues; Root cause analysis
What They're Looking For.
Must Have
8+ years infrastructure development, Production critical systems ownership, AWS or GCP expertise, Proficient in Python, Build tooling and automation, Kubernetes experience, Docker experience, Container orchestration experience, Infrastructure as Code experience, Git-based workflows, Solid Linux fundamentals, Cross-team initiative leadership, Clear communication, Empathetic communication, Mentoring engineers, Data-informed decision making
Nice to Have
AWS preferred, GCP preferred, Python preferred, Terraform preferred, Experience in regulated environments, Healthcare or healthtech experience, Platform engineering background, Security engineering background, Access control experience, Encryption experience, Auditability experience, Compliance experience, ML/data teams experience, ML platforms experience, Airflow experience, Ray experience, ML pipelines experience, Model serving stacks experience, Observability stacks familiarity, Internal developer platforms experience, SDKs experience, Reusable frameworks experience, Startup scaling experience
How You'll Work.
Team & Collaboration
Collaborating across functions; Work closely with Platform leadership; Work closely with product engineering; Work closely with data teams; Work closely with ML teams; Partnering with engineering leadership; Collaborate with security stakeholders; Collaborate with compliance stakeholders; Collaborate with technical partners; Collaborate with non-technical partners
Communication Scope
Communicate tradeoffs; Communicate clearly; Communicate empathetically
Process & Methodology
Roadmaps, Sequencing work
Full Job Description
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 https://www.radai.com/news/auntminnie-recognizes-rad-ai-omni-reporting-as-2023s-best-new-radiology-software, and ranked by Deloitte https://www2.deloitte.com/us/en/pages/technology-media-and-telecommunications/articles/fast500-winners.html 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 https://www.cnbc.com/2025/06/10/2025-cnbc-disruptor-50-see-the-full-list-of-companies.html 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 The Platform Engineering organization at Rad AI builds the foundations that power all of our products—Reportin
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