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Qa Engineer

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Remote

Qa Engineer

Pylon Management Consulting

Qa Engineer

Skills

Testing & QAAI

2 months ago

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Important information


Contract type:

Permanent

Location:

Nagpur, Maharashtra, India

Work mode:

Remote

Published on:

4 September 2026

What they need


Job Description: QA Engineer / Test Lead

Experience Required: 4-6 Years
Notice Period: Immediate Joiners Only

Role Overview

We are seeking an experienced QA Engineer / Test Lead responsible for enabling the client's QA engineers and test leads to apply AI across the testing lifecycle.

The role will focus on:

  • AI test-case generation
  • Regression-test optimization
  • Defect triage
  • Synthetic test-data generation
  • Exploratory-testing ideation
  • Bug-report quality improvement

Key Responsibilities

  • Enable QA engineers and test leads to apply AI across the testing lifecycle.
  • Delivery training on AI test-case generation.
  • Support regression-test optimization initiatives.
  • Drive defect triage activities.
  • Facilitate synthetic test-data generation.
  • Guide exploratory-testing ideation using AI.
  • Improve bug-report quality through AI-assisted approaches.
  • Promote the effective use of GenAI to accelerate testing without compromising coverage or control.

Required Experience & Skills

  • 4-6 years of experience in QA Engineering or Test Engineering.
  • Strong QA background with experience in manual and automated testing.
  • Understanding of test-management processes and defect lifecycle management.
  • Experience with enterprise quality practices.
  • Exposure to AI and GenAI tools used within testing environments.
  • Strong understanding of the differences between traditional QA practices and AI-enabled QA approaches.
  • Knowledge of AI test-case generation, test optimisation, and AI-assisted testing techniques.
  • Practical experience using GenAI to accelerate testing while maintaining quality, coverage, and control.
  • Good communication and stakeholder management skills.
  • Ability to clearly explain AI concepts and tools to engineering and business stakeholders.

Note: Candidates must have AI exposure, strong communication skills, an understanding of AI tools, and appreciation of the differences between non-AI QA and AI-enabled QA practices.

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