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Rad AI is transforming healthcare with AI-driven radiology solutions. Founded by a radiologist, the company has secured over $140M in funding (Series C: $68M, valuation $528M) and is backed by Khosla Ventures, Gradient Ventures, and others. Rad AI's AI supports more than one-third of radiology groups and healthcare systems and nearly 50% of all medical imaging in the U.S., helping thousands of radiologists daily uncover new diagnoses and reduce error rates by nearly 50%.
The Platform Engineering organization builds the foundations powering all Rad AI products (Reporting, Impressions, Continuity). The Infrastructure team owns core cloud infrastructure, platforms, and reliability practices. As a Senior Software Engineer, you will architect and evolve cloud infrastructure primarily on AWS (Kubernetes, ECS, Lambda, EC2, data stores), collaborate with engineering leadership and product partners to shape platform vision, develop tooling to improve developer experience and productivity, promote sustainable incident response and blameless post-incident reviews, and manage network/systems monitoring with alert strategy design and on-call rotation participation.
You will contribute to infrastructure architecture, reliability practices, and thoughtful improvements to engineering workflows. This is an individual contributor role with mentoring responsibilities—you'll guide others in technical design while executing independently on project-level work.
REQUIREMENTS:
- 6+ years of hands-on infrastructure/platform development experience in modern, cloud-native environments, with a track record of owning critical systems in production
- Extensive production Kubernetes experience, including cluster lifecycle management, scaling, and container security
- Proficiency in Python (preferred) and/or Bash; familiarity with Infrastructure as Code tools (CDK, Terraform, Pulumi)
- Strong AWS and/or GCP experience
- Networking fundamentals and comfort with command-line Linux environments
- Clear communication and collaboration skills; 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
- Data-informed approach and track record of effective problem solving
NICE TO HAVES:
- Deep Linux troubleshooting (kernel, driver issues)
- Experience in regulated environments (HIPAA) or early-stage startups
- Healthcare, security, or machine learning background
- Familiarity with HL7 or radiology workflows
- OpenTelemetry or similar tracing services
- Grafana or similar logging services
- Spark (EMR, Dataproc, HDInsight) and Hadoop-related technologies
