Senior Infrastructure Engineer

Engineering · Full-time · United States

Job description

About Rad AI

We have raised $80+ million to date from venture funds and just closed on our series B financing with investors Khosla Ventures, Gradient (Google’s AI fund) and ARTIS. We’ve also formed a partnership with Google to collaborate on the future of generative AI to redefine healthcare. Currently, more than 1/3 of radiology groups and healthcare systems, including Kaiser Permanente, HCA Healthcare, and Geisinger, now leverage the latest Gen AI advancements from Rad AI. We're recognized as one of the most promising healthcare AI companies by both CB Insights and AuntMinnie. Come join us in transforming healthcare with AI!

Founded by the youngest US radiologist in history, Rad AI empowers physicians with Al to save time, reduce burnout, and improve the quality of patient care. By combining our deep expertise in healthcare and AI and using one of the largest proprietary radiology report datasets in the world, our AI has uncovered hundreds of new cancer diagnoses for patients and reduced the error rate in tens of millions of radiology reports by nearly 50%. 

Why Join Us:

We're on the lookout for a Senior Infrastructure Engineer with a focus on DevOps to join our engineering team. In this role, you'll play a pivotal part in architecting a robust, scalable infrastructure, elevating our system reliability practices, and driving innovation in our workflows. If you're passionate about creating resilient systems and enjoy collaborating with cross-functional teams, this role is perfect for you.

Responsibilities:

  • Architect and build infrastructure for our platform, utilizing container orchestration tools (preferably Kubernetes), serverless applications (e.g., Lambda), virtual machines like EC2 (or equivalents in GCE or Azure), and databases.
  • Collaborate closely with engineering leaders, machine learning, data science, and product teams to define our Platform vision.
  • Develop and maintain efficient tooling to enhance the productivity of our engineering team.
  • Promote sustainable incident response practices and conduct blameless postmortems.
  • Oversee network and systems monitoring, devise alert strategies, and join a 24x7 five-engineer on-call rotation.

Requirements:

  • A data-driven approach with a knack for quick and effective problem resolution.
  • Minimum 7 years of infrastructure experience with proficiency in Python (preferred), Bash, IaC (Terraform, Pulumi) and/or other industry-standard languages.
  • Strong familiarity with AWS and/or GPC services.
  • Networking expertise and comfort working with command-line Linux.
  • Exceptional communication, organizational, delegation, and feedback skills.
  • Ability to design complex systems and mentor others in technical design.
  • Proficiency in deep Linux troubleshooting, including debugging kernel and driver issues.
  • Ability to scope project level work and execute independently, bringing projects to completion.

Nice to Have:

  • Experience in regulated environments (e.g., HIPAA compliance) 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 Graylog or analogous logging services.
  • Experience working with Spark (EMR, DataProc, HD Insights) and Hadoop-related technologies.

Come join our world-class team as we build and deploy AI solutions that will make a difference in millions of people’s lives. Our team is mission-driven and focused on transparency, inclusion, close collaboration, and building an incredible team.

If you're passionate about driving innovation and delivering impactful reporting solutions, we'd love to hear from you!

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
  • Location-flexibility (remote-first company!)
  • Flexible PTO policy
  • Annual company-wide offsite
  • Periodic team offsites
  • Annual equipment stipend

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.

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