QA Automation Engineer

Roles and Responsibilities

• Design, develop, and maintain automation frameworks for Salesforce applications, web applications, APIs, and data validation scenarios 

• Create reusable automation components, utilities, shared libraries, and maintainable framework solutions aligned with industry best practices 

• Leverage AI-enabled tools responsibly to improve automation development, test design, and productivity 

• Validate critical end-to-end business processes across integrated enterprise applications 

• Collaborate with engineering, product, business stakeholders, and subject-matter experts to translate requirements into automated test coverage 

• Develop, execute, and maintain regression suites for high-risk and business-critical workflows 

• Integrate automated tests into CI/CD pipelines and support test reporting and quality gates 

• Manage test data, dependencies, and environment readiness to ensure reliable execution 

• Support functional, integration, regression, and release validation activities 

• Document test strategies, automation coverage, assumptions, and known risks 

• Contribute to continuous improvement of QA processes, automation frameworks, and engineering practices 

Education & Experience

• Bachelor’s degree in Computer Science, Engineering, Information Technology, or equivalent practical experience 

• 5–6 years of hands-on experience in QA automation for enterprise web applications, Salesforce platforms, or integrated business systems 

Required Skills & Qualifications 

Must Have 

• 5–6 years of experience in test automation for enterprise applications 

• Proven experience developing and maintaining automation frameworks, reusable components, shared libraries, and utilities 

• Hands-on experience with Playwright for UI and end-to-end automation testing 

• Experience testing Salesforce applications and business workflows 

• Working knowledge of Salesforce platform concepts and integrated enterprise workflows 

• Experience with UI, API, regression, integration, and end-to-end test automation 

• Strong JavaScript/TypeScript skills for automation development 

• Experience integrating automation suites with CI/CD pipelines 

• Knowledge of test data management and validation techniques 

• Strong debugging, analytical, and problem-solving skills 

• Experience working in Agile environments and collaborating with QA, Engineering, Product, and Business teams 

• Effective written and verbal communication skills 

• Ability to quickly learn new tools, technologies, and automation frameworks 

Preferred Qualifications

• Experience working with Salesforce Clouds and cross-application business processes 

• Exposure to enterprise automation tools such as Copado Robotic Testing, Provar, Tricentis Tosca, Cypress, or similar platforms 

• Experience with API automation, SQL queries, and data validation 

• Exposure to containerized test execution environments and cloud-based test infrastructure 

• Practical experience using AI-assisted development tools to improve test automation efficiency and maintainability 

• Understanding of automation metrics, test coverage analysis, and execution reporting 

Soft Skills 

• Strong ownership and accountability 

• Quality-first mindset with attention to detail 

• Agile and adaptable approach to problem-solving 

• Collaborative and team-oriented mindset 

• Ability to evaluate tools and solutions pragmatically based on business needs and maintainability 

• Strong organizational and prioritization skills 

• Continuous learning mindset with interest in emerging automation and AI technologies 

AI Automation & Proficiency

• Working knowledge of AI-assisted tools and workflows (e.g., generative AI assistants, AI-powered coding/testing tools, or agentic AI platforms) relevant to the role's core function. 

• Ability to apply effective prompting techniques to accelerate research, documentation, coding, or analysis tasks. 

• Comfortable learning and adopting new AI-enabled tools as part of day-to-day work, with a willingness to continuously build AI fluency. 

• Understanding of responsible AI use, including data privacy, security, and verification of AI-generated outputs before acting on them.