Quality Assurance / Software Test Engineer (AI-Assisted Testing & Automation)

Position: Quality Assurance / Software Test Engineer (AI-Assisted Testing &  Automation)

Location: San Antonio, TX (Onsight & In Person Interview)

Essential duties include the following:
• Design and create risk-based test plans, test scenarios, and traceable test cases from business and technical requirements.
• Execute manual and automated tests, report defects, analyze failures, and accurately document results and evidence.
• Update and enhance reusable test suites, automation frameworks, and test methods to improve coverage, reliability, and maintainability.
• Create, manage, and, where appropriate, automate test-data setup and cleanup using approved tools and environments.
• Identify quality, delivery, data, security, and automation risks that may affect the schedule, and recommend mitigation actions.
• Provide clear, concise project, test, automation, and quality documentation.
• Contribute to requirements, specifications, test case, automation code, and test plan reviews.
• Collaborate with developers, business analysts, product owners, DevOps engineers, and other SIT professionals to solve problems and improve testability.
• Participate in the documentation, development, and continuous improvement of quality engineering processes, standards, and procedures.
• Build positive working relationships within and across departments.
• Proactively strengthen technical, automation, AI, and domain knowledge.
• Follow established organizational processes, security requirements, data-handling standards, and responsible AI practices.
• Use approved generative AI and agentic tools, including Kiro, to assist with test scenario generation, automation code creation, framework scaffolding, documentation, and failure analysis, with human review of generated outputs.
• Develop and maintain automated tests for web, API, database, and end-to-end workflows using tools such as Playwright or Selenium and appropriate service-testing frameworks.
• Apply codebase-aware and requirements-aware techniques to identify coverage gaps, edge cases, negative scenarios, and potential drift between requirements, implementation, and automated tests.
• Integrate automated testing into CI/CD pipelines and support continuous testing through reliable quality gates, reporting, traces, logs, screenshots, and other diagnostic artifacts.
• Evaluate and improve automation resilience through stable locator strategies, reusable components, data-driven design, retry-aware assertions, and appropriate self-healing or AI-assisted maintenance techniques.
• Support testing of AI-enabled features by validating functional behavior, accuracy, reliability, security, privacy, explainability, bias risks, and appropriate human oversight when applicable.
• Use production-like telemetry and defect trends, when authorized, to prioritize regression coverage and strengthen shift-left and shift-right quality practices.

Minimum Qualifications:
• Bachelor’s degree in Computer Science, Information Technology, Engineering, or a related technical field from an accredited college or university, or equivalent relevant experience, required.
• Minimum of three (3) years of software testing or quality engineering experience, including static, system, regression, functional, non-functional, exploratory, and performance testing.
• Experience testing modern web applications and distributed systems.
• Proficient Microsoft Office skills, including Outlook, Word, and Excel.
• Experience with API testing tools and practices, such as Postman, SoapUI, or automated REST API validation.
• Experience with Agile software delivery practices using Scrum and/or Kanban preferred.
• Strong understanding of testing fundamentals, including risk-based testing, requirements traceability, defect management and analysis, test design techniques, defect prevention, and remediation validation.
• Understanding of relational data models and data integrity concepts.
• Working knowledge of SQL and relational databases, such as SQL Server or PostgreSQL.
• Basic software development skills in at least one language, with the ability to read, troubleshoot, and maintain automated test code.
• Basic understanding of AWS or another cloud platform preferred.
• Experience querying databases for test-data creation and retrieval and evaluating the performance of basic queries.
• Experience with test management, source control, CI/CD, and defect reporting tools such as Azure DevOps, Jira, or similar platforms.
• Ability to remain current with evolving testing methods, automation frameworks, AI-assisted engineering practices, and responsible AI expectations.
• Exposure to external data sources and storage systems, including file shares, databases, object storage, APIs, and flat files.
• Hands-on experience creating or maintaining test automation using Playwright, Selenium, or a comparable framework.
• Experience using AI-assisted development or testing tools, such as Kiro or comparable coding assistants, to generate, review, debug, or maintain test assets preferred.
• Understanding of generative AI limitations and the need to validate AI-generated test cases, code, locators, assertions, test data, and documentation before use.
• Familiarity with modern AI-in-testing patterns such as requirements-to-test generation, risk-based test prioritization, agentic workflow validation, synthetic test-data generation, intelligent failure triage, and automation maintenance preferred.
• Experience with Playwright MCP, Selenium MCP, Model Context Protocol integrations, or other browser-aware AI automation approaches is a plus.
• Ability to review automation code for completeness, maintainability, security, reliable assertions, stable selectors, and alignment with established framework standards.
• Demonstrate initiative and innovation.
• Strong interpersonal skills.
• Strong verbal and written communication skills.