Description

Job Responsibilities include:

Design and implement reusable agentic test automation frameworks, reference architectures, and best practices to enable scalable quality engineering across multiple development teams.

Develop AI-powered testing solutions for automated test generation, test maintenance, failure analysis, and quality insights using LLMs, GitHub Copilot, Playwright, and Karate.

Define testing standards, coverage strategies, governance models, and quality gates to improve software quality, traceability, and release readiness.

Build and integrate automated review agents that assess requirements, user stories, and development artifacts for completeness, quality, risk, and compliance.

Develop centralized reporting and analytics solutions that aggregate test, application, and CI/CD data to provide actionable insights, trend analysis, and GenAI-driven summaries.

Collaborate with engineering, product, and quality teams to drive adoption of AI-enabled testing practices, improve developer productivity, and enhance software delivery processes.

Required Qualifications:

Bachelor’s degree in computer science, Software Engineering, Information Technology, Artificial Intelligence, or a related technical field.

8+ years of experience in Test Automation, Quality Engineering, Software Development, or Automation Architecture, with hands-on experience in GenAI-enabled engineering solutions.

Strong expertise in Agentic AI, LLM-powered automation, GitHub Copilot, GitHub Actions, Playwright, Karate, and designing enterprise-scale test automation frameworks and quality engineering strategies.

Proven experience building AI-driven testing solutions, automated quality gates, cross-service reporting platforms, CI/CD integrations, and governance frameworks that improve software quality, release readiness, and engineering productivity

Key Skills

Education

Any Graduate