Senior Quality Assurance Lead, Quality Engineering Transformation

Sorenson Communications is a language services provider delivering communication, interpreting, translation, and captioning solutions. The Senior Quality Assurance Lead will establish a modern QA Center of Excellence using automation and AI, define quality standards and testing strategies, integrate quality gates into CI/CD, and improve engineering-wide ownership of quality. The role will also mentor QA professionals and developers, create quality reporting systems, and lead quality engineering transformation initiatives.

Responsibilities:

• Define and lead the vision for a modern QA Center of Excellence that uses automation and AI to reduce reliance on manual validation and embed quality throughout the software development lifecycle
• Establish quality standards, testing strategy, automation architecture, and release-readiness criteria across UI, API, integration, regression, exploratory, and non-functional testing
• Build and evolve AI-assisted QA workflows, including test generation, requirements-to-test traceability, failure analysis, defect triage, risk-based regression selection, and automation maintenance
• Partner with developers to shift testing left by improving acceptance criteria, testability, unit/integration coverage, PR-level validation, and developer-owned automation
• Integrate automated tests and quality gates into CI/CD pipelines so teams receive fast, reliable feedback before merge, during nightly runs, and before release
• Create quality dashboards and reporting systems that show product health, automation coverage, regression status, defect trends, flaky tests, release risk, and improvement opportunities
• Design a nightly automated QA pipeline capable of running against product codebases, identifying failures, filing actionable bugs, and publishing quality status without manual pass/fail documentation
• Lead the evaluation, selection, and responsible use of QA tools, AI-enabled testing platforms, automation frameworks, test data approaches, and reporting systems
• Mentor QA team members and developers in automation-first, AI-enabled quality practices, building team capability rather than centralizing all testing work inside QA
• Partner with Product, Engineering, DevOps, and leadership to prioritize quality investments, communicate release risk, and continuously improve the organization's quality engineering practices

Requirements:

• Minimum 4 Year / Bachelors Degree Computer Science, Information Systems, Software Engineering, Computer Engineering, or a related technical field; or equivalent practical experience
• 4 years Experience in software quality assurance, quality engineering, SDET, test automation, or software engineering roles, including hands-on experience designing, building, or maintaining automated test frameworks
• 2 years Technical leadership experience defining QA strategy, improving automation practices, mentoring QA engineers or developers, integrating quality gates into CI/CD pipelines, or leading quality engineering transformation initiatives
• Strong hands-on experience with modern test automation for UI, API, integration, regression, and end-to-end testing using tools such as Playwright, Cypress, Selenium, Postman, PyTest, or similar frameworks
• Experience integrating automated tests into CI/CD pipelines such as GitHub Actions, GitLab, Jenkins, Azure DevOps, or similar platforms
• Ability to define an automation-first quality strategy that reduces manual validation and increases developer ownership of testing
• Practical understanding of AI-assisted quality engineering, including AI-supported test generation, failure analysis, defect triage, requirements-to-test traceability, risk-based regression selection, and automation maintenance
• Strong programming or scripting ability in languages such as TypeScript, JavaScript, Python, Java, or similar languages used for test automation and tooling
• Experience designing quality dashboards, release-readiness metrics, defect trend reporting, automation coverage reporting, and other feedback systems that make product health visible
• Ability to partner effectively with Product, Engineering, DevOps, QA, and leadership to clarify requirements, identify risk early, and embed quality practices throughout the software development lifecycle
• Strong understanding of shift-left testing, testability, acceptance criteria, exploratory testing, nonfunctional testing, and release risk assessment
• Ability to mentor QA team members and developers in automation-first, AI-enabled quality practices without centralizing all testing responsibility inside QA
• Strong written and verbal communication skills, including the ability to explain quality risk, tradeoffs, and improvement opportunities to both technical and non-technical stakeholders
• Travel Requirements: Less than 25%
• Software testing, test automation, quality engineering, AI-assisted testing, DevOps, cloud platforms, or Agile software delivery