Quality Engineer 3

Ensure data integrity and isolation in AI-driven workflows

Demonstrate strong proficiency in prompt engineering to effectively leverage AI tools for accelerating test design, execution, and analysis.

Design and implement AI-driven testing solutions using techniques such as Skills, Cursor Rules, and Retrieval-Augmented Generation (RAG) to improve accuracy and efficiency.

No Escaped defect for production releases

Build and maintain scalable, end-to-end automated testing frameworks to validate AI model-based integrations across frontend UI, backend microservices, and data layers.

Ensure frameworks are robust, reusable, and aligned with system architecture and performance needs.

Strong hands-on experience with Playwright (TypeScript/JavaScript)

Knowledge of automation design patterns (Page Object Model, fixtures)

CI/CD pipelines

Establish and optimize AI based CI/CD pipelines, ensuring continuous validation of models and integration workflows.

Implement effective production monitoring strategies to track model performance, detect anomalies, and ensure system reliability.

Experience with tools such as JMeter or k6

Design AI driven Load and Performance Testing

Understanding of metrics such as response time, throughput, error rate, and concurrency

Experience with CI/CD tools (Jenkins, GitHub Actions, Azure DevOps)

Proficiency with Git and version control workflows

Basic understanding of microservices architecture and cloud environments

Act as a bridge between Data Scientists, Software Engineers, and Product Managers to ensure seamless delivery of AI-enabled features.

Drive alignment on quality goals, testing strategies, and release readiness.

Identify and analyze complex issues such as model drift, data inconsistencies, and system failures.

Recommend architectural or data-driven improvements rather than limiting contributions to defect reporting.

Nice to Have

Experience testing AI/GenAI-based products or features

Familiarity with AI frameworks, workflows, or agent-based systems

Experience building or contributing to internal QA tools or platforms

Exposure to test analytics, quality metrics, and data-driven QA practices

Experience and Qualifications 7-10 years of experience in QA or Software Testing Proven experience in AI in testing, automation and performance testing using AI agents and IDEs like Cursor or integrate Copilot, Cowork, Claude etc Should have worked on AI IDEs or tools like CoPilot, Cursor, or similar Experience testing SaaS, web-based applications for enterprise products Ability to balance quality with delivery timelines with Zero Escaped Defect Mentor QE team members Strong analytical and problem-solving abilities Clear and structured communication with cross-functional teams Ownership mindset with attention to detail

7-10 years of experience in QA or Software Testing

Proven experience in AI in testing, automation and performance testing using AI agents and IDEs like Cursor or integrate Copilot, Cowork, Claude etc

Should have worked on AI IDEs or tools like CoPilot, Cursor, or similar

Experience testing SaaS, web-based applications for enterprise products

Ability to balance quality with delivery timelines with Zero Escaped Defect

Mentor QE team members

Strong analytical and problem-solving abilities

Clear and structured communication with cross-functional teams

Ownership mindset with attention to detail

Don’t have all the skills/experience mentioned above? At Granicus, we are trying to build diverse, inclusive teams. We do not have degree requirements for most of our roles. If you don’t meet every requirement above but are excited to learn more, we encourage you to apply. We might just be able to find another role that could be a perfect fit!