Senior Test Engineer (Remote Opportunity)

VetsEZ•Atlanta, GA

1d•Remote

About The Position

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.

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.
U.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.

Nice To Haves

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.

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.