Mid-Level Quality Engineer

New

JobgetherSoftware Development

BrazilFull-TimeMiddle

Salary not disclosed

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Job Details

Professional experience in Quality Engineering, Software Testing, Test Automation, or a related discipline.
Proficiency with test automation tools and frameworks.
Practical knowledge of RESTful APIs and web technologies.
Strong analytical and problem-solving skills, with a structured approach to identifying and investigating defects.
Experience with scripting or programming languages such as Python or JavaScript.
Understanding of CI/CD processes, pipelines, and related tools.
Ability to work collaboratively with engineering and product teams throughout the development lifecycle.
Strong attention to detail and a proactive mindset focused on preventing defects.
Ability to perform root-cause analysis and communicate technical findings clearly to stakeholders.
Experience with cloud services such as AWS or Azure is a plus.
Familiarity with Artificial Intelligence and Machine Learning concepts is desirable.
Experience with performance testing tools is an advantage.

Own and continuously evolve the quality strategy for the webhook-based integration solution.
Develop a deep understanding of the existing codebase, architecture, APIs, integrations, and business workflows.
Design and execute functional, integration, API, regression, and end-to-end testing activities.
Develop, maintain, and improve automated test suites across appropriate layers of the application.
Validate webhook events, payloads, responses, retries, error handling, and failure scenarios.
Test integrations between dependent systems and proactively identify potential integration risks.
Validate authentication, authorization, permissions, and relevant security scenarios.
Define quality gates and establish clear criteria for release readiness.
Identify defects as early as possible and collaborate with engineering teams to diagnose and resolve issues.
Conduct root-cause analysis and contribute to initiatives that improve overall product quality.
Use AI-powered engineering capabilities to support test design, automation, codebase analysis, and quality improvement.
Contribute to scalable quality practices and continuous improvements across the software development lifecycle.

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