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Senior Technical Program Manager

Rad AI · San Francisco, United States

External listingfull-timeabout 1 month ago

About The Role

Join Rad AI as a Senior Technical Program Manager, where you'll lead the delivery of our innovative radiology reporting product. You'll work closely with engineering, design, implementations, and clinical teams to drive the product roadmap and ensure successful client integration and deployment. This role requires strong technical skills, experience in healthcare IT, and the ability to communicate effectively with both technical and non-technical stakeholders. Enjoy a comprehensive benefits package, including health, dental, and vision coverage, flexible PTO, and stock options.

  • Assurer la livraison des programmes pour Rad AI Reporting, en dirigeant la feuille de route du produit et en menant les programmes d'intégration et de déploiement des clients.
  • Coordonner la livraison de nouvelles intégrations de fournisseurs à grande échelle en collaborant avec les ressources de déploiement et d'ingénierie.
  • Établir des playbooks, runbooks et tableaux de bord KPI répétables pour rendre les intégrations plus rapides, plus prévisibles et mesurables.
  • EHR integration: Familiarity with how orders and results flow between EHR, RIS, PACS, and reporting/dictation systems, and where integration points commonly break
  • Technical skills — integration diagnosis & troubleshooting (required)
  • Experience building KPI frameworks and executive-ready reporting to quantify productivity, quality, and adoption
  • Diagnostic toolkit: Comfortable reading application and interface logs, using API testing tools (e.g. Postman), inspecting network connectivity (VPN/firewall, ports, TLS), and writing basic queries or scripts (SQL, light Python/shell) to investigate issues
  • HL7 v2: Able to read and interpret message structure (MSH, PID, OBR, OBX, ORM/ORU segments), spot malformed or missing fields, and trace where a message fails in the pipeline
  • 6+ years as a Technical Program Manager in a software or healthcare-IT environment, with a track record delivering complex, cross-functional programs from inception through launch
  • Bachelor's degree in Computer Science, Engineering, or a related technical field (or equivalent experience)
  • Strong analytical and pragmatic problem-solving skills with sound technical judgment
  • Clinical workflow context: Understands radiology reporting and speech/dictation workflows well enough to reason about how an integration defect shows up for an end-user radiologist
  • This role requires someone who can independently read an interface spec, inspect a live message, and isolate where a failing integration is breaking — not just route tickets
  • Excellent communication and presentation skills — able to translate between deeply technical engineers and non-technical clinical or IT stakeholders
  • Interface engines: Hands-on experience with Mirth Connect, Rhapsody, or Cloverleaf — tracing messages, reading channel logs, and understanding routing and transformation
  • Demonstrated experience managing customer-facing integration and deployment programs, including health-system or enterprise go-lives
  • DICOM & PACS/RIS: Working knowledge of DICOM objects and key tags, study/series/instance hierarchy, and how worklist (MWL) and image/report flow moves through PACS and RIS systems
  • FHIR: Comfortable with REST APIs, common resources (Patient, DiagnosticReport, ImagingStudy, ServiceRequest), JSON/XML payloads, and reading API/auth errors — OAuth2 and SMART on FHIR a plus
  • Enterprise healthcare delivery experience in regulated environments, with working knowledge of HIPAA, PHI handling, and SOC 2 practices
  • Track record leading complex integrations and go-lives with large health systems or radiology groups, including security reviews and cross-vendor dependencies
  • Exposure to clinical AI regulatory considerations — risk management, documentation, and when/where FDA or other approvals may apply
  • Change-management experience with radiologist end users
  • Experience collaborating with AI/ML engineering teams

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