We are seeking a professional
QA Engineer (SaaS)
who takes clear ownership of product quality within a modern SaaS environment. This is a hands-on role embedded directly in the SDLC, working closely with Product, Engineering, and DevOps to ensure releases are stable, predictable, and production-ready.

The ideal candidate demonstrates strong curiosity about how systems fail, discipline in validating that they work, and the ability to clearly communicate risk. You will design and execute comprehensive test strategies—including positive, negative, regression, integration, API, performance, and baseline security testing—while supporting both manual and automated approaches.

This role also involves building and managing large-scale synthetic test data, integrating automated tests into CI/CD pipelines, leveraging AI-powered QA tools, and continuously improving quality standards and processes. Success is measured by reduced production defects, reliable releases, and increased confidence in system stability.

Requisitos

• 
  3–5+ years of hands-on QA experience in production SaaS environments.

• 
  Strong experience designing and executing positive, negative, and regression test strategies.

• 
  Proven ability to create and manage synthetic test data at scale.

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  Experience testing APIs, integrations, and complex multi-step workflows.

• 
  Solid expertise in manual and exploratory testing for web-based SaaS applications.

• 
  Experience with API testing tools (Postman, REST-based services).

• 
  Experience supporting or extending automated test suites using Selenium, Cypress, or Playwright.

• 
  Familiarity with integrating automated testing into CI/CD pipelines (GitHub Actions, Jenkins, or similar).

• 
  Exposure to performance testing tools (JMeter, Locust, or similar).

• 
  Understanding of SaaS-specific quality considerations such as multi-tenancy, scalability, and backward compatibility.

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  Working knowledge of Agile methodologies and continuous delivery environments.

• 
  Strong written communication skills for defect reporting and release validation.

Nice to Have:

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  Experience improving QA frameworks, standards, and tooling strategies.

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  Exposure to cloud environments (AWS, Azure, or GCP).

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  Experience with AI-driven testing platforms (test generation, self-healing automation, analytics).

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  Mentorship or leadership experience within QA teams.