Payjoy

QA Engineer

Salario competitivo

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Habilidades

Python, PHP, AWS.

Modalidad

Remoto Global

¿Inglés?

Sí, Avanzado

Responsabilidades

🤓 As a QA Engineer, the company expects you to perform the following tasks:

  • Experience testing LLM/NLP-powered chatbots to ensure natural, context-aware, and accurate interactions.
  • Strong understanding of intent recognition and fallback handling within conversational AI environments.
  • Ability to validate IVR flows (e.g., Talkdesk) with a focus on voice logic, flow accuracy, and user experience.
  • Proficiency in end-to-end testing of integrations (e.g., Zendesk), ensuring data consistency and platform reliability.
  • Experience defining scalable QA processes, with an emphasis on automation-readiness and continuous improvement.
  • Skilled in writing detailed test cases and regression suites for conversational and voice interfaces.
  • Ability to collaborate cross-functionally with product managers, engineers, and conversation designers.
  • Familiarity with automated testing tools and scripts, especially for APIs and regression coverage.
  • Experience conducting User Acceptance Testing (UAT) and simulating real-user interactions for both chat and voice.
  • Strong documentation and reporting skills, including tracking defects, test coverage, and model behavior insights.



Requisitos

You are the person they are looking for if you have....

  • Bachelor’s degree in Computer Science, Engineering, or a related field — or equivalent practical experience.
  • At least 2 years of QA experience, ideally testing AI-powered applications, chatbots, or conversational systems.
  • Hands-on experience with LLM/NLP-based systems (e.g., GPT, Dialogflow, Rasa) is highly preferred.
  • Familiarity with IVR testing (Talkdesk or similar) and platforms like Zendesk.
  • Strong knowledge of QA methodologies, test case design, and defect tracking tools (e.g., Jira, TestRail).
  • Experience with automation tools such as Selenium, Postman, or Cypress.
  • Understanding of NLP/LLM concepts, including intents, entities, prompt testing, and model behavior.
  • Excellent communication skills and ability to collaborate cross-functionally, documenting findings clearly.

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