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Rad AI

Generative AI radiology workflow automation platform

Senior Technical Support Engineer

Customer SupportConfirmed live in the last 24 hours
Full-time$86k - $115k /yrRemote

About the Job

Requirements

  • Availability to work West Coast hours, 4:00 pm to 2:00 am PST, Wednesday through Saturday, providing partial overnight customer coverage.
  • At least 6 years in customer-facing technical roles supporting enterprise SaaS, with at least 2 years as a senior or lead escalation resource.
  • Hands-on healthcare IT experience with HL7 v2 messaging (ORU/ORM/ADT), interface engines, and PACS/RIS or dictation workflows in a radiology or hospital setting.
  • Ability to debug web and desktop applications in complex Windows enterprise environments, including log analysis, network and VPN troubleshooting, and SSO and identity issues involving SAML, Azure AD, Okta, or ADFS.
  • Experience mentoring or coaching support engineers and raising team performance without direct authority.
  • Ability to provide clear updates and take customer-facing ownership during incidents, including communicating with physicians, IT administrators, and executives and remaining composed under pressure with many open issues.
  • Comfort working in a fast-moving startup where processes are still being built, and willingness to document and systematize what is learned.

Responsibilities

  • Serve as the senior technical escalation point for complex, multi-system issues involving the Reporting platform, HL7 and integration layer (Interlinx, Medplum), speech recognition, and customer Windows/PACS environments; drive issues to root cause rather than workaround.
  • Own high-visibility customer incidents by leading the technical support response during P1/P2 events, coordinating with Engineering on-call, running customer-facing bridges, and delivering post-incident reviews and root-cause analyses on time.
  • Lead technical support coverage for enterprise go-lives, including readiness reviews with Implementations, hypercare, and handoff to steady-state support.
  • Drive ticket quality and SLA attainment across the team through triage standards, escalation criteria, and Zendesk/Linear workflow design; identify volume drivers and work with Product and Engineering to eliminate them.
  • Build and maintain runbooks, troubleshooting guides, and Help Center content for new products and integrations; raise the team’s technical capabilities through mentoring, shadowing, and ticket reviews.
  • Partner with the automation and AI workstream to design, test, and roll out triage, classification, and self-service tools that reduce manual ticket handling.
  • Represent Technical Support in Engineering triage, incident review, and release planning, bringing customer impact data to prioritization decisions.
  • Participate in and help lead the on-call rotation, including occasional night and weekend coverage, and contribute to the design of 24/7 coverage as the team scales.

Desired Qualifications

  • Experience with speech recognition or clinical documentation products.
  • Scripting or querying skills in SQL, Python, or PowerShell for log analysis, data pulls, and light automation; exposure to workflow tools such as n8n or Tray.
  • Experience with observability and alerting tools such as Better Stack, Datadog, or similar, or with FHIR/Medplum.
  • Strong command of Zendesk, including triggers, SLAs, views, and reporting, and Linear or equivalent; experience designing support workflows rather than only working within them.
  • Prior experience at a radiology practice, teleradiology group, radiology-focused software company, or a similarly focused healthcare field.
  • Experience supporting multi-site enterprise health system deployments or working directly with Implementations or Professional Services.

About the Company

Rad AI

Generative AI radiology workflow automation platform

Rad AI builds AI-powered tools for radiology to streamline clinical workflows. Its enterprise SaaS platform integrates with existing radiology software to automate reporting and follow-up processes. Core products include Rad AI Reporting (generates radiology reports tailored to a radiologist’s style), Rad AI Impressions (summaries of dictated findings), and Rad AI Continuity (automated follow-up management for incidental findings). The company targets large health systems and leading radiology practices, aiming to reduce physician burnout and improve patient care by speeding up documentation and standardizing follow-up.

Company size
201-500
Company stage
Series C
Total funding
$147M
Headquarters
San Francisco, CA
Founded
2018

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