Solutionara Private Limited is hiring a QA Engineer – Quality Engineering & Automation to support quality assurance across enterprise applications, APIs, integrations, and digital solutions delivered from our Noida Global Delivery Center.
This is a hands-on quality engineering role that combines manual testing and test automation. We are looking for someone who does more than execute predefined test cases: you understand how a solution works, identify where it could fail, investigate defects, automate repeatable testing, and communicate quality risks clearly to the delivery team.
Location: Noida, Uttar Pradesh (on-site). Experience: 3–6 years. Employment: full-time.
About Solutionara
Solutionara is a U.S.-based IT Consulting and Technology Services firm with a Global Delivery Center in Noida, India. We operate with high ownership, lean teams, and disciplined execution, and we are evolving toward an AI-enabled delivery model focused on enterprise integration, digital transformation, and scalable technology solutions for global clients.
What You’ll Do
Analyze requirements, user stories, and acceptance criteria, and turn them into test scenarios, test cases, and test data.
Execute functional, regression, integration, system, smoke, exploratory, and end-to-end testing, including negative, boundary, and data-validation cases.
Develop and maintain automated test scripts for web applications and APIs, contribute to existing frameworks, and reduce flaky tests.
Debug failed automation and distinguish application defects from automation, test-data, and environment issues.
Test REST APIs and system integrations using Postman or equivalent: payloads, status codes, headers, authentication, error handling, and retries.
Use SQL to validate data consistency across UI, APIs, databases, and integrated systems.
Document clear, reproducible defects with evidence, severity, and business impact; take part in triage and root cause analysis.
Support release readiness with smoke and sanity testing before and after deployments across QA, UAT, staging, and production.
Work closely with Developers, QA Leads, Project Managers, Business Analysts, and DevOps in Agile ceremonies, raising blockers and quality risks early.
Use approved AI-assisted tools responsibly for test-case generation, automation, test data, and defect analysis, validating outputs before use.
Required Qualifications
3–6 years of hands-on Software QA / Quality Engineering experience, covering both manual testing and test automation.
Strong understanding of SDLC and STLC.
Experience with an automation tool or framework such as Selenium, Playwright, Cypress, or equivalent.
Working programming or scripting knowledge in Java, JavaScript/TypeScript, Python, or another automation language.
Hands-on REST API testing using Postman or comparable tools.
Working knowledge of SQL and database validation.
Experience with defect and test-management tools such as Jira, Azure DevOps, TestRail, Zephyr, or Xray.
Familiarity with Git and a basic understanding of CI/CD and automated testing in delivery pipelines.
Understanding of HTTP, REST, JSON, authentication, and web application architecture.
Experience in Agile/Scrum or hybrid delivery environments.
Strong analytical skills, clear defect documentation and communication, ownership, and attention to detail.
Preferred Qualifications
Experience in IT consulting, technology services, or Global Delivery Center environments, supporting U.S. or other global clients.
Experience testing enterprise applications, integrations, cloud solutions, data platforms, eCommerce, PIM/DAM, ERP, or CRM.
Exposure to AWS and/or Azure, Docker, and CI/CD tools such as Jenkins, GitHub Actions, GitLab CI, or Azure DevOps.
Exposure to performance testing (JMeter, k6) and basic application-security concepts (OWASP).
Experience with AI-assisted engineering or testing tools.
Relevant QA or testing certifications are beneficial but not mandatory.
What Success Looks Like
Requirements are translated into meaningful coverage that goes beyond the happy path.
Defects are found early and documented with sufficient technical evidence.
Automated regression coverage grows in meaningful, maintainable areas, and automation failures are investigated rather than rerun until they pass.
API, database, and integration testing complement UI testing.
Risks and blockers are communicated early, and releases receive disciplined pre- and post-deployment validation.
Assigned testing activities are owned independently through completion.