Senior Software Engineer, Infrastructure

The Platform Engineering organization at Rad AI builds the foundations that power all of our products-Reporting, Impressions, and Continuity-and enables product teams to ship reliably, safely, and at scale. Within Platform, the Infrastructure team owns our core cloud infrastructure, platforms, and reliability practices. We’re hiring a Senior Software Engineer to help us design and operate robust, scalable systems. In this role, you’ll contribute to infrastructure architecture, reliability practices, and thoughtful improvements to our workflows. If you’re passionate about building resilient platforms and enjoy collaborating across functions, we’d love to hear from you., * Architect and evolve our cloud infrastructure (primarily on AWS) across container orchestration (Kubernetes, Elastic Container Service), serverless (e.g., Lambda), virtual machines (e.g., EC2), and data stores to support current and future products.

• Collaborate with engineering leadership, machine learning, data science, and product partners to help shape our platform vision.
• Develop and maintain tooling that improves engineering productivity and developer experience.
• Promote sustainable incident response and lead blameless post-incident reviews.
• Manage network and systems monitoring, design alert strategies, and participate in an equitable on-call rotation.

• A data-informed approach and a track record of effective problem solving.
• Bring 6+ years of hands-on infrastructure / platform development experience (or equivalent practical experience) in modern, cloud-native environments, with a track record of owning critical systems in production.
• Extensive experience operating Kubernetes in production, including familiarity with cluster lifecycle management, scaling, and container security.
• Proficiency in one or more languages-Python (preferred) and/or Bash-and familiarity with Infrastructure as Code (IaC) tools such as CDK, Terraform or Pulumi.
• Strong familiarity with AWS and/or GCP services.
• Networking fundamentals and comfort working in command-line Linux environments.
• Clear, respectful communication and collaboration skills, including organizing work, delegating when appropriate, and giving/receiving feedback.
• Experience designing complex systems and mentoring others in technical design.
• Ability to scope project-level work, execute independently, and bring projects to completion while collaborating with teammates.

Nice to Haves:

• Proficiency in deep Linux troubleshooting, including debugging kernel and driver issues.
• Experience in regulated environments (e.g., HIPAA) or at early-stage startups.
• Background in healthcare, security, or machine learning.
• Familiarity with HL7 or radiology workflows.
• Experience with OpenTelemetry or similar tracing services.
• Familiarity with Grafana or similar logging services.
• Experience with Spark (e.g., EMR, Dataproc, HDInsight) and Hadoop-related technologies.

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!

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 no-reply@ashbyhq.com.

Compensation Range: $160K - $215K

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!, 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!, 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