Senior Test Engineer

New
V
VetsEZFederal Healthcare IT
The candidate must reside within the continental US.Full-TimeSenior
Salary not disclosed
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Job Details

Experience
Minimum of 5 years of experience testing healthcare software applications.
Required Skills
AgileRESTful APIsGenerative AI

Requirements

  • Bachelor’s degree in Computer Science, Information Technology, Health Informatics, Engineering, or a related technical discipline, or equivalent experience.
  • Minimum of 5 years of experience testing healthcare software applications.
  • Strong knowledge of Consolidated Clinical Document Architecture (C-CDA) standards.
  • Hands-on experience reading, validating, and troubleshooting XML-based healthcare data.
  • Experience with healthcare interoperability standards and clinical data exchange.
  • Experience testing Clinical Decision Support (CDS) applications and workflows.
  • Familiarity with SMART on FHIR, CDS Hooks, and REST APIs.
  • Experience with test automation frameworks, API testing tools, and defect management platforms.
  • Experience developing and maintaining automated testing solutions within Agile and DevSecOps environments.
  • Experience with AI-assisted testing tools and techniques.
  • Familiarity with Generative AI and Large Language Models (LLMs).
  • Experience validating AI-generated outputs and establishing quality controls.

Responsibilities

  • Develop comprehensive test plans, test cases, and acceptance criteria for AI-powered patient summarization capabilities.
  • Design test coverage across clinical document types, including CCD, Discharge Summaries, and Progress Notes.
  • Analyze and validate C-CDA XML documents, verifying accurate extraction of clinical information.
  • Ensure AI-generated summaries maintain traceability to original clinical sources.
  • Develop and maintain automated test suites for document ingestion, AI summarization, APIs, and user interfaces.
  • Support CI/CD pipelines through automated quality gates and continuous testing.
  • Build automated validation frameworks for AI-generated summaries.
  • Evaluate AI-generated content for clinical completeness, consistency, and reliability.
  • Participate in defect triage, root-cause analysis, and release-readiness activities.
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