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Scienceabode > Python Quality Engineer

Python Quality Engineer

Last updated: 2025/08/18 at 8:01 AM
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  • Permanent
  • United States
  • Posted 2 weeks ago
Calsoft Labs

Website Calsoft Labs

Calsoft Labs

Company : Calsoft Labs

Role: Python Quality Engineer
Location: Remote

About Us
We are building a cutting-edge voice and chat platform for natural, responsive user interaction. Our systems operate at scale, with strong integration and performance demands. We're looking for a Python QA Engineer to ensure the platform's reliability, scalability, and user experience.

Role Overview:
As a Python Quality Engineer, you'll develop and maintain test automation frameworks, create simulation tools for testing, and drive quality throughout the software development lifecycle. This includes APIs, backend services, and system integrations.

Key Responsibilities:

  • Build and maintain Python-based automation frameworks for backend systems
  • Develop test suites for APIs, integration flows, and backend services
  • Simulate real-world use cases and conversational scenarios for system testing
  • Contribute to CI/CD pipelines and quality assurance processes
  • Collaborate closely with developers and product teams to ensure high-quality releases

Qualifications:

  • 5+ years of experience in Python-based test automation
  • Strong understanding of API and integration testing
  • Experience with asynchronous service testing and mocking tools
  • Familiarity with distributed systems and backend integration testing
  • Bonus: Exposure to AI/LLM testing or interest in gaining such experience

What We're Looking For:

  • Strong grasp of software testing principles and best practices
  • Collaborative team player comfortable in agile environments
  • Strong attention to detail and a problem-solving mindset
  • Experience with modern development tools (e.g., containers, CI/CD)
  • Ability to work in agile, cross-functional teams
  • Strong communication skills and a collaborative mindset

Our Technical Environment Includes:

  • Python-based frameworks for testing and automation
  • Asynchronous APIs and backend microservices
  • CI/CD pipelines and containerized environments
  • Limited use of AI APIs and language model platforms

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