Senior QA Engineer – AI Platforms & Automation

Sumcircle Technologies Pvt. Ltd.

United States

Remote

USD 120,000 - 150,000

Full time

4 days ago
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Job summary

Sumcircle Technologies Pvt. Ltd. is seeking an experienced QA Engineer for AI Platforms & Enterprise QA.

The role focuses on ensuring quality, reliability and production readiness of enterprise AI platforms, including multimodal workflows, through comprehensive testing strategies and automation. Responsibilities include designing test plans, automating regression suites, validating AI outputs, and collaborating with product, engineering and architecture teams to mitigate quality risks throughout

Qualifications

  • 8-10 years of QA experience in AI platforms or enterprise-grade software.
  • Strong scripting and test automation background.
  • Experience validating AI/multimodal outputs and model endpoints.

Responsibilities

  • Develop end-to-end QA strategy and release-quality criteria for AI platform capabilities.
  • Document and maintain functional, API, integration, workflow, regression test cases.
  • Translate requirements into test scenarios including edge cases and adversarial inputs.
  • Validate AI workflows, business rules, orchestration logic and human-in-the-loop flows.
  • Build and integrate automated regression suites into CI/CD pipelines.
  • Perform API validation across internal services and third-party integrations.
  • Measure performance, scalability and reliability under production-like loads.
  • Track defects with clear reproduction steps and impact assessment.

Skills

Python programming
SQL data validation
Test automation
API testing
CI/CD pipelines

Tools

Postman
Swagger/OpenAPI

Job description

Sumcircle Technologies Pvt. Ltd. is seeking an experienced QA Engineer for AI Platforms & Enterprise QA.

The role focuses on ensuring quality, reliability and production readiness of enterprise AI platforms, including multimodal workflows, through comprehensive testing strategies and automation. Responsibilities include designing test plans, automating regression suites, validating AI outputs, and collaborating with product, engineering and architecture teams to mitigate quality risks throughout

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