Senior Automation Engineer (Remote Opportunity)

• →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.

• 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.

• 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.

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.