Senior Technical Support Engineer, Mobile

RapidAI is the trusted leader in deep clinical AI, helping hospitals deliver faster, more informed care through intelligent imaging and integrated workflows. The Rapid Enterprise™ Platform supports disease states across the care spectrum, but it’s our clinical depth that drives the most meaningful impact — improving decision-making, patient outcomes, and health-system performance. Used by more than 2,500 hospitals in over 100 countries and backed by 700+ clinical studies, including research that helped expand national stroke-treatment guidelines, RapidAI is the most clinically validated AI platform in healthcare.

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• 7–10 years of experience in Linux systems engineering.

• 7–10 years working with Kubernetes, Docker, and container orchestration.

• Strong background in virtualization: VMware, Nutanix, Hyper-V.

• Experience with cloud-native storage technologies (e.g., Rook/Ceph).

• Proficient in Python scripting for automation and tooling.

• Demonstrated expertise in infrastructure as code using tools like Terraform and Ansible.

• Experience with network troubleshooting and diagnostic tools. 

• Familiarity with healthcare imaging systems, DICOM routers, and Vendor Neutral Archives (VNA) is highly desirable.

• Proven ability to lead and mentor high-performing teams for at least 5 years. 

 

 

 • Lead the design, deployment, and maintenance of infrastructure in AWS and hybrid cloud environments.

 • Drive platform modernization using Kubernetes, Docker, and Linux-based systems.

 • Oversee integration of virtualization technologies including VMware, Nutanix, and Hyper-V.

 • Implement and manage cloud-native storage solutions such as Rook/Ceph.

 • Develop automation using tools such as Terraform and Ansible.

 • Collaborate with engineering teams to ensure production readiness of new features and services—on both cloud and on-prem          deployments.

• Troubleshoot complex infrastructure and network issues; utilize tools like Wireshark to identify and resolve performance                     bottlenecks.

• Support edge computing platforms and work closely with app teams to understand how infrastructure choices impact personas,       workflows, and integrations.

• Collaborate with support and engineering to reproduce, triage, and resolve customer issues across infrastructure layers.

• Use emerging technologies including AI-driven tooling to enhance observability, productivity, and scalability of platform operations.

• Contribute to the evolution of a customer-obsessed culture, mentoring and developing junior engineers and platform specialists.