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QA Engineer

Sutherland
Chennai, IND
Full Time, Temporary
Senior · 5+ years experience
Onsite
Discovered 1 months ago

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Company Description:

About Sutherland

Artificial Intelligence. Automation.Cloud engineering. Advanced analytics.For business leaders, these are key factors of success. For us, they’re our core expertise.

We work with iconic brands worldwide. We bring them a unique value proposition through market-leading technology and business process excellence.

We’ve created over 200 unique inventions under several patents across AI and other critical technologies. Leveraging our advanced products and platforms, we drive digital transformation, optimize critical business operations, reinvent experiences, and pioneer new solutions, all provided through a seamless “as a service” model.

For each company, we provide new keys for their businesses, the people they work with, and the customers they serve. We tailor proven and rapid formulas, to fit their unique DNA.We bring together human expertise and artificial intelligence to develop digital chemistry. This unlocks new possibilities, transformative outcomes and enduring relationships. Sutherland

Unlocking digital performance. Delivering measurable results.

Role Summary

Owns technical testing of agent outputs — accuracy, turnaround-time impact, and regression testing as agents are iterated — feeding the accuracy and completion-time KPIs tracked at the programme level.

Key Responsibilities

  • Build test suites validating agent outputs against golden-record datasets across covered processes.
  • Track and report accuracy/turnaround-time metrics to support baselining exercises agreed with the business.
  • Run regression testing whenever agent/prompt configurations change, to prevent silent accuracy drift in regulated processes.
  • Feed findings into the human QA function for final sign-off — this role supports human QA authority on regulated activity with technical evidence, not replaces it.

Required Experience

5+ years QA/test engineering experience, ideally including ML/LLM output validation (not just deterministic software testing).

Experience defining test datasets and accuracy benchmarks for document/text-processing systems.

Domain process familiarity a plus for building realistic test scenarios.

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