QA Automation Engineer

Job description

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.