VetsEZ is currently looking for a
Senior Test Engineer for a 100% remote position supporting a large federal government healthcare modernization project. In this role, you will support the development, validation, and automation of an AI-powered Patient Health Data Summarization capability within the Joint Longitudinal Viewer (JLV) Clinical Decision Support (CDS) platform. The ideal candidate will have strong healthcare interoperability experience, knowledge of C-CDA standards, experience testing complex healthcare applications, and hands-on experience with test automation and AI-enabled quality engineering.
The candidate must reside within the continental US.
Responsibilities- Develop comprehensive test plans, test cases, and acceptance criteria for AI-powered patient summarization capabilities.
- Create traceability between business requirements, clinical data standards, and test scenarios.
- Design test coverage across clinical document types, including Continuity of Care Documents (CCD), Discharge Summaries, Progress Notes, and History & Physical documents.
- Develop positive, negative, boundary, and edge-case testing scenarios for AI-enabled clinical applications.
- Analyze and validate C-CDA XML documents, including headers, sections, templates, and clinical entries.
- Verify accurate extraction and summarization of clinical information, including medications, allergies, laboratory results, procedures, care plans, and diagnoses.
- Ensure AI-generated summaries accurately reflect source clinical documentation and maintain traceability to original clinical sources.
- Perform functional, integration, system, regression, performance, and user acceptance testing.
- Develop and maintain automated test suites for document ingestion, AI summarization, APIs, and user interfaces.
- Test CDS workflows and patient-context-driven launch scenarios across multiple data sources and patient encounters.
- 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, usability, accuracy, and reliability.
- Identify omissions, inaccuracies, hallucinations, and other AI-generated defects that could impact clinical workflows.
- Validate AI guardrails, monitoring capabilities, auditability, and quality controls.
- Participate in defect triage, root-cause analysis, and release-readiness activities.
- Create test documentation, defect reports, traceability matrices, and quality assessments.
- Collaborate with software engineers, solution architects, clinicians, product owners, cybersecurity teams, and government stakeholders.
- Leverage AI-assisted tools to accelerate test development, test automation, regression testing, defect analysis, and quality assurance activities.
- Take on additional tasks and responsibilities as needed to support team objectives and ensure the success of the project.
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, including clinical document structure, sections, templates, and entries.
- 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, REST APIs, and related interoperability technologies.
- 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 for test case generation, automation development, regression testing, defect analysis, and quality assurance.
- Familiarity with Generative AI and Large Language Models (LLMs), including using AI to create and maintain automated test scripts, validation frameworks, and test data.
- Experience validating AI-generated outputs and establishing quality controls for accuracy, consistency, repeatability, and reliability.
- Strong analytical, troubleshooting, and problem-solving skills.
- Excellent written and verbal communication skills.
Additional Qualifications- Experience supporting Department of Veterans Affairs (VA) healthcare systems, including JLV or similar clinical viewer applications.
- Knowledge of USCDI and healthcare interoperability requirements.
- Familiarity with healthcare terminologies such as SNOMED CT, LOINC, RxNorm, and ICD.
- Experience validating AI/ML-enabled healthcare solutions.
- Experience with AI-powered testing platforms such as GitHub Copilot, Microsoft Copilot, Testim, Functionize, Mabl, or similar tools.
- Experience creating autonomous or semi-autonomous AI testing workflows, including test-case generation, coverage analysis, synthetic test data, and automated defect triage.
- Understanding of prompt engineering and AI evaluation methodologies for software quality assurance.
- Knowledge of accessibility and usability testing within healthcare environments.
- Experience working within Agile, DevSecOps, and cloud-native development environments.
- Exposure to healthcare data analytics and modernization initiatives within federal healthcare agencies.
Security Clearance RequirementsU.S. Citizenship is required.
All selected candidates must successfully complete a background check.
Ability to obtain and maintain a Government/Public Trust clearance, including required fingerprinting, when required for the position.
Benefits- Medical/Dental/Vision.
- 401k with Employer Match.
- PTO + Federal Holidays.
- Corporate Laptop.
- Training Opportunities.
- Remote Opportunity.
