Senior SQA Automation Engineer

Senior SQA Automation Engineer

Department: Software Engineering

Experience: 6-10 years (minimum 4 in hands-on test automation)

Employment Type: Full-Time

About the Role

ReBiz is hiring a hands-on Senior SQA

Automation Engineer to build and own scalable test automation across our web,

desktop, and mobile applications, APIs, and backend services.

AI-assisted testing is a core requirement

of this role, not an add-on. You will use AI tools daily to generate, review,

and maintain tests, and you will help validate the AI-enabled features in our

products.

We are looking for an engineer with

strong programming fundamentals, clear ownership, and a track record of

improving how quality is engineered.

Key Responsibilities

1. Test Automation & Quality Engineering

• Design, build, and maintain

scalable automation frameworks for web, desktop, and mobile applications, APIs,

and backend services.

• Automate functional, regression,

integration, and end-to-end tests, and integrate them into CI/CD pipelines.

• Validate REST APIs, third-party

integrations, scheduled jobs, and asynchronous processes.

• Test desktop and mobile

applications across supported operating systems, devices, and versions, including

installation, upgrade, and offline behavior.

• Validate application behavior

during migrations, upgrades, and deployments, and support performance and

failure-recovery testing.

• Investigate complex defects and

work with developers on root-cause analysis.

2. Data & Database Testing

• Perform SQL-based data

verification, reconciliation, and reporting validation.

• Test database logic, including

stored procedures, functions, triggers, and views, for correctness, edge cases,

error handling, and performance.

• Validate ETL processes and data

pipelines end to end, including source-to-target mapping, transformation logic,

and data synchronization workflows.

• Implement automated data quality

checks for completeness, accuracy, duplicates, null handling, and referential

integrity.

• Validate schemas and data

contracts to catch breaking changes between services and upstream sources.

• Manage test data, including

generation, seeding, and masking or anonymization, so that no real customer

data is used in test environments.

• Test system behavior and query

performance at realistic data volumes.

3. AI-Assisted Testing

• Use AI-assisted tools (e.g.,

GitHub Copilot, Claude, ChatGPT) as part of daily work to generate test cases,

write automation code, and maintain existing suites.

• Review all AI-generated test code

for correctness, assertion strength, maintainability, and security before it is

merged.

• Apply AI to failure analysis,

flaky-test triage, and regression suite optimization.

• Test AI-enabled product features

for output accuracy, consistency, and reliability, including building

evaluation datasets and prompt-based regression checks.

• Evaluate emerging AI testing tools

and adopt those that deliver measurable gains.

• Follow responsible-use practices:

no customer, production, or confidential data is entered into external AI

tools.

4. Release Quality & Process

• Own test planning and test

strategy for assigned products, applying risk-based testing to critical

business workflows.

• Define and maintain automated

quality gates in CI/CD that block releases failing agreed criteria.

• Drive release-readiness

assessments, defect triage, and regression analysis.

• Track and report quality metrics,

including automation coverage, flaky-test rate, and defect leakage to

production.

• Identify testing gaps and

implement improvements to QA practices.

5. Collaboration

• Work with Development, DevOps,

Product Management, and SQA teams on testability and automation architecture.

• Share automation techniques and

AI-assisted testing practices with colleagues.

• Communicate test outcomes, risks,

and recommendations clearly to stakeholders.

Required Skills

Test Automation & Engineering

• Strong programming skills in at

least one of TypeScript/JavaScript, Python, Java, or C#.

• Hands-on experience with

Playwright, Selenium, or Cypress, including designing and maintaining

automation frameworks.

• Hands-on experience testing and

automating desktop or mobile applications, using tools such as Appium,

WinAppDriver, FlaUI, Espresso, or XCUITest.

• Strong REST API automation

experience using code-based tools such as Playwright API testing, REST Assured,

Pytest, or Postman with Newman.

• Strong SQL skills, including

testing stored procedures, functions, and triggers, and validating data across

relational databases.

• Experience testing ETL processes

or data pipelines, including source-to-target validation and automated data

quality checks.

• Experience with test data

management, including data generation, seeding, and masking of sensitive data.

• Experience with Git and CI/CD

tools such as GitHub Actions, GitLab CI, or Jenkins.

• Experience with functional,

regression, integration, end-to-end, and exploratory testing.

• Understanding of Agile/Scrum

practices and the software development lifecycle.

• Strong debugging, analytical, and

problem-solving skills.

AI Competency (Mandatory)

• Demonstrated hands-on use of

AI-assisted development tools (e.g., GitHub Copilot, Claude, ChatGPT) in

production test automation work, with examples of measurable impact on

coverage, speed, or maintenance effort.

• Ability to critically review

AI-generated code and identify incorrect logic, weak assertions, brittle

locators, and security issues.

• Working knowledge of prompting

techniques for test generation, and of AI tool limitations such as

hallucination and non-deterministic output.

• Practical experience validating

LLM-based features or AI-generated outputs, including output validation, prompt

testing, and regression datasets.

• Understanding of safe AI usage,

including data privacy and confidentiality when using external AI tools.

Preferred Skills

• Experience with AI-augmented

testing platforms, such as self-healing tests or visual AI testing.

• Experience with AWS, Docker, and

microservices-based applications.

• Exposure to performance testing

tools such as JMeter or k6.

• Experience with analytics

platforms, BI tools, and reporting systems.

• Knowledge of application security

testing and OWASP principles.

Professional Competencies

• Strong ownership and

accountability.

• Analytical thinking and

independent problem-solving.

• Effective collaboration with

cross-functional engineering teams.

• Clear written and verbal

communication.

• Ability to prioritize work across

multiple projects.

• Willingness to mentor colleagues

and share technical knowledge.

• Adaptability to emerging

technologies, particularly AI-driven engineering practices.

Qualifications

• Bachelor's degree in Computer

Science, Software Engineering, or a related field, or equivalent practical

experience.

• 6-10 years of professional

experience in software quality assurance, including at least 4 years building

and maintaining automation frameworks.

• Demonstrated record of improving

automation coverage and testing processes.

• Experience working with

cross-functional engineering teams on complex software applications.