Job Summary

QA Engineer with a robust focus on AI-driven quality engineering and test automation to help improve product quality, accelerate testing, and drive the adoption of AI across the QA lifecycle.

The role will be responsible for designing and implementing robust test strategies, expanding automation coverage, and leveraging Generative AI/LLMs and AI-powered tools to improve test case generation, test execution, defect detection, and overall QA efficiency.

Key Responsibilities

- Design, develop, and execute comprehensive test strategies for product features and releases.
- Build and maintain scalable automated test frameworks and regression suites.
- Leverage AI/LLMs to generate test cases, identify edge scenarios, analyze requirements, and improve test coverage.
- Explore and implement AI-driven QA tools and workflows to reduce manual testing effort and improve productivity.
- Integrate automated tests into CI/CD pipelines and improve test execution efficiency and reliability.
- Identify, troubleshoot, and track defects, working closely with Engineering, Product, and DevOps teams.
- Drive shift-left testing and early defect detection throughout the software development lifecycle.
- Monitor automation quality, reduce flaky tests, and continuously improve test reliability.
- Contribute to release qualification, quality gates, and continuous improvement of QA processes.
- Analyze production/customer issues and implement preventive testing strategies.




- Stay current with emerging AI technologies and identify opportunities to apply them to software quality engineering.

Requirements

- 5+ years of experience in Software Quality Assurance and test automation.
- Strong experience with automation frameworks and programming languages such as Python, Java, or JavaScript/TypeScript.
- Experience with API, UI, integration, and end-to-end testing.
- Strong understanding of CI/CD, Git, and modern software development practices.
- Hands-on experience using Generative AI/LLMs or AI-powered development/testing tools.
- Strong analytical, debugging, and problem-solving skills.
- Excellent communication and collaboration skills.

Preferred Qualifications

- Experience building AI-assisted or AI-powered QA solutions.
- Experience with cloud platforms such as AWS, Azure, or GCP.
- Experience with Docker/Kubernetes and cloud-native applications.
- Experience integrating automation into CI/CD pipelines such as GitHub Actions.
- Experience testing security, data, SaaS, or enterprise applications.
- Familiarity with AI agents, prompt engineering, RAG, or LLM evaluation/testing.
- Success in this role will be measured by increased automation and test coverage, reduced test authoring and execution time, lower automation flakiness, earlier defect detection, and a measurable reduction in customer-reported defects.

Disclaimer: This job posting has been aggregated from external source. Role details, content, and availability are subject to change. Applicants are advised to confirm the latest information directly on the company website before applying.

📌 Sr. QA Automation Engineer (Bengaluru)
🏢 Proofpoint
📍 Bengaluru