QA Automation Engineer
🇮🇳 India
Cypress
Management
JavaScript
TypeScript
Salesforce
Machine Learning
Design
UI/UX
Devops
SQL
Testing
QA Automation Engineer
from 🇮🇳 India
Roles and Responsibilities
Design, develop, and maintain automation frameworks for Salesforce applications, web applications, APIs, and data validation scenariosÂ
Create reusable automation components, utilities, shared libraries, and maintainable framework solutions aligned with industry best practicesÂ
Leverage AI-enabled tools responsibly to improve automation development, test design, and productivityÂ
Validate critical end-to-end business processes across integrated enterprise applicationsÂ
Collaborate with engineering, product, business stakeholders, and subject-matter experts to translate requirements into automated test coverageÂ
Develop, execute, and maintain regression suites for high-risk and business-critical workflowsÂ
Integrate automated tests into CI/CD pipelines and support test reporting and quality gatesÂ
Manage test data, dependencies, and environment readiness to ensure reliable executionÂ
Support functional, integration, regression, and release validation activitiesÂ
Document test strategies, automation coverage, assumptions, and known risksÂ
Contribute to continuous improvement of QA processes, automation frameworks, and engineering practicesÂ
Education & Experience
Bachelor’s degree in Computer Science, Engineering, Information Technology, or equivalent practical experienceÂ
5–6 years of hands-on experience in QA automation for enterprise web applications, Salesforce platforms, or integrated business systemsÂ
Required Skills & QualificationsÂ
Must HaveÂ
5–6 years of experience in test automation for enterprise applicationsÂ
Proven experience developing and maintaining automation frameworks, reusable components, shared libraries, and utilitiesÂ
Hands-on experience with Playwright for UI and end-to-end automation testingÂ
Experience testing Salesforce applications and business workflowsÂ
Working knowledge of Salesforce platform concepts and integrated enterprise workflowsÂ
Experience with UI, API, regression, integration, and end-to-end test automationÂ
Strong JavaScript/TypeScript skills for automation developmentÂ
Experience integrating automation suites with CI/CD pipelinesÂ
Knowledge of test data management and validation techniquesÂ
Strong debugging, analytical, and problem-solving skillsÂ
Experience working in Agile environments and collaborating with QA, Engineering, Product, and Business teamsÂ
Effective written and verbal communication skillsÂ
Ability to quickly learn new tools, technologies, and automation frameworksÂ
Preferred Qualifications
Experience working with Salesforce Clouds and cross-application business processesÂ
Exposure to enterprise automation tools such as Copado Robotic Testing, Provar, Tricentis Tosca, Cypress, or similar platformsÂ
Experience with API automation, SQL queries, and data validationÂ
Exposure to containerized test execution environments and cloud-based test infrastructureÂ
Practical experience using AI-assisted development tools to improve test automation efficiency and maintainabilityÂ
Understanding of automation metrics, test coverage analysis, and execution reportingÂ
Soft SkillsÂ
Strong ownership and accountabilityÂ
Quality-first mindset with attention to detailÂ
Agile and adaptable approach to problem-solvingÂ
Collaborative and team-oriented mindsetÂ
Ability to evaluate tools and solutions pragmatically based on business needs and maintainabilityÂ
Strong organizational and prioritization skillsÂ
Continuous learning mindset with interest in emerging automation and AI technologiesÂ
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.Â
Ability to apply effective prompting techniques to accelerate research, documentation, coding, or analysis tasks.Â
Comfortable learning and adopting new AI-enabled tools as part of day-to-day work, with a willingness to continuously build AI fluency.Â
Understanding of responsible AI use, including data privacy, security, and verification of AI-generated outputs before acting on them.Â
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