QA Automation Engineering Manager

We are seeking a highly skilled QA Automation Manager to lead Quality Assurance Automation team. This role is pivotal in ensuring the quality, scalability, and reliability of industry-leading CLM platform. The ideal candidate will have a proven track record in managing QA teams, building and maintaining automation frameworks, and collaborating with cross-functional engineering teams to deliver high-quality software at scale.

Job Responsibilities:

Leadership & Team Management

• Lead and mentor a team of QA Automation Engineers, fostering a culture of accountability, innovation, and continuous improvement.
• Define clear roles, responsibilities, and career paths for QA team members.
• Recruit, train, and retain top talent in QA automation.

QA Strategy & Execution

• Own the QA automation strategy and ensure alignment with the overall product and engineering roadmap.
• Establish and maintain robust automation frameworks to support frequent SaaS releases on global scale.
• Maintain and expand effective CI/CD testing processes, ensuring automation coverage across multiple layers of the application (UI, API, backend, AI).
• Ensure quality assurance automation is integrated into the SDLC from requirements to release.

Collaboration & Stakeholder Management

• Partner closely with Product Management, Engineering, and DevOps teams to define acceptance criteria, quality goals, and release metrics.
• Work with engineering leadership to define and implement testing standards, KPIs, and success metrics.
• Act as the voice of efficient quality assurance across the organization and make tools and systems available that enable QA efficiency.

Process & Quality Improvements

• Champion test automation best practices, tools, and technologies to reduce the manual testing overhead.
• Continuously assess and improve QA processes to optimize efficiency and effectiveness.
• Oversee test data management, test environments, and defect tracking.
• Ensure compliance with industry standards and enterprise security requirements.
• Other duties as assigned

Required qualifications

• Bachelors degree in Computer Science, Engineering, or related field (or equivalent experience).
• 7+ years of experience in software testing/QA, with at least 3+ years in QA leadership/management roles.
• Strong expertise in test automation frameworks (e.g., Selenium, Cypress, Playwright)
• Hands-on experience with CI/CD pipelines (e.g., Jenkins, GitLab CI, GitHub Actions).
• Solid understanding of enterprise SaaS applications, microservices, and cloud platforms (Preferred: AWS).
• Proven experience in scaling automation frameworks for large, distributed applications.
• Excellent leadership, communication, and collaboration skills.
• Experienced at working in a globally distributed team in a remote-only environment.

Preferred Qualifications

• AI/ML in QA: Experience applying AI-powered tools for test design, test creation, defect prediction, root-cause analysis, and self-healing automation scripts.
• Intelligent Test Automation: Familiarity with AI-driven testing platforms and their application in the enterprise software development environment.
• Data-Driven QA: Ability to leverage analytics and predictive modeling to optimize test coverage, prioritize test cases, and measure release quality.
• Industry Best Practices: Deep knowledge of QA standards and modern approaches like shift-left and continuous testing.
• Exploratory & Autonomous Testing: Knowledge of using AI-enhanced exploratory testing and robotic process automation (RPA) for regression-heavy workflows.
• Scalable Test Architecture: Expertise in designing maintainable frameworks that integrate automated functional, performance, security, and reliability testing.
• Cloud-Native QA: Experience with containerized test environments (Docker, Kubernetes) and service virtualization.
• Performance & Reliability Engineering: Experience with relevant quality assurance approaches, such as chaos testing and resilience testing.
• Modern Collaboration Tools: Skilled in integrating QA workflows into DevOps toolchains.
• Innovation Leadership: Proven ability to evaluate, adopt, and implement emerging technologies, such as AI copilots, LLM-based test generation, and intelligent defect tracking.