Quality Software Engineer

Quality Software Engineer

5+ Years Experience

Role Overview

We are seeking a Quality Software Engineer with 5+ years of experience to contribute to the quality engineering of enterprise-grade AI and SaaS products. The ideal candidate should have strong hands-on experience in manual testing, test automation, API testing, database testing, and regression testing .

The candidate will work closely with Engineering, Product, and QA teams to understand requirements, design effective test scenarios, identify defects, improve test coverage, and support high-quality software releases.

Experience in product engineering, SaaS applications, AI/ML-driven applications, data-intensive platforms, or regulated software will be an advantage.

Key Responsibilities

1. Functional & Manual Testing

• Strong understanding of SDLC (Software Development Life Cycle) and STLC (Software Testing Life Cycle) .
• Create and execute test scenarios, test cases, and test plans based on product requirements.
• Perform functional, regression, smoke, sanity, exploratory, usability, integration, and acceptance testing .
• Analyze requirements and identify functional gaps, edge cases, dependencies, and potential quality risks .
• Execute tests across different environments and configurations.
• Log, track, retest, and close defects using JIRA or similar defect management tools .
• Perform root-cause analysis of defects in collaboration with developers.
• Participate in requirement reviews, story grooming, sprint planning, and release activities .
• Work closely with developers and Product teams to ensure defects are resolved within the required timelines.

2. Automation Testing

• Hands-on experience in UI and API test automation .
• Experience with automation frameworks/tools such as Playwright, Selenium, Cypress, or similar technologies .
• Good programming/scripting knowledge in Python, Java, JavaScript, or TypeScript .
• Develop, execute, and maintain reusable and maintainable automation scripts .
• Identify suitable test cases for automation and contribute to improving automation coverage .
• Troubleshoot and analyze automation failures.
• Experience with headless browser testing is preferred.
• Understanding of parallel test execution is an advantage.
• Basic experience integrating automated tests with CI/CD pipelines such as Jenkins, GitHub Actions, or GitLab CI.
• Experience with Git, Bitbucket, or similar version-control tools .
• Knowledge of BDD frameworks such as Cucumber or SpecFlow is an advantage.

3. API Testing

• Hands-on experience in REST API testing using tools such as Postman .
• Validate API responses, status codes, request/response parameters, headers, and error handling.
• Test positive, negative, boundary, and error scenarios .
• Validate API integration with databases and downstream services.
• Basic understanding of authentication and authorization mechanisms such as JWT and OAuth.
• Experience creating and maintaining API automation tests is preferred.

4. Data & Database Testing

• Good hands-on experience with SQL and database testing .
• Experience with databases such as MySQL, PostgreSQL, MongoDB, or Cassandra .
• Ability to write SQL queries for data validation, reconciliation, and integrity checks .
• Validate data across different application layers and services.
• Experience testing data transformation, migration, and data consistency .
• Understanding of ETL/data pipelines and data lake concepts is an advantage.
• Ability to identify and troubleshoot data-related defects .

5. Performance & Non-Functional Testing

• Understanding of performance, load, stress, reliability, and scalability testing .
• Hands-on experience with JMeter or similar performance testing tools.
• Exposure to BlazeMeter or cloud-based performance testing is an advantage.
• Ability to analyze response time, throughput, latency, and performance trends .
• Basic understanding of identifying performance bottlenecks .
• Exposure to monitoring and logging tools such as Grafana, Prometheus, ELK, or Splunk .
• Understanding of test data generation and parameterization for performance testing.
• Basic understanding …