Full Description

At GoML, we design and build cutting-edge Generative AI, AI/ML, and Data Engineering solutions that help businesses unlock the full potential of their data, drive intelligent automation, and create transformative AI-powered experiences. Our mission is to bridge the gap between state-of-the-art AI research and real-world enterprise applications – helping organizations innovate faster, make smarter decisions, and scale AI solutions seamlessly.

We’re looking for a QA Automation Engineer with deep expertise in automation frameworks, data validation, CI/CD pipelines, and end-to-end testing strategies. In this role, you’ll lead our quality engineering efforts, build scalable automation systems, and ensure our AI-powered platforms are reliable, high-performing, and production-ready. If you’re passionate about building robust automation, breaking complex systems, and elevating engineering quality standards, we’d love to hear from you!

Why You? Why Now?

As AI adoption scales across enterprises, the need for flawless, secure, and high-performance systems becomes critical. This role is ideal for someone who loves automating every aspect of the SDLC, building efficient QA pipelines, and ensuring product excellence across AI/ML-powered platforms.

What You’ll Do (Key Responsibilities)

First 30 Days: Foundation & Orientation

Deep dive into GoML’s AI/ML & GenAI products, platforms, and engineering workflows Understand existing QA processes, automation frameworks, and deployment pipelines Review current testing coverage, gaps, and data validation workflows Collaborate with engineering teams to understand product functionality and quality goals

First 60 Days: Execution & Impact

Design and develop scalable automation frameworks for web, API, data, and backend systems Implement automated test suites integrated with CI/CD pipelines (GitHub Actions, GitLab, Jenkins, etc.) Drive API testing, performance testing, and end-to-end validation strategies Build utilities and scripts for test data generation and manipulation Collaborate with backend, ML, and DevOps teams to ensure testability and continuous quality

First 180 Days: Ownership & Transformation

Own QA strategy across multiple engineering teams and product lines Establish best practices for automation coverage, data validation, and release readiness Implement AI-assisted testing approaches (model-based testing, anomaly detection, etc.) Optimize pipelines for faster feedback loops and improved reliability Mentor QA engineers and build a high-performing automation team Contribute to the quality roadmap for enterprise-grade AI platforms

What You Bring (Qualifications & Skills)

Must-Have

5+ years of experience in QA & Test Automation Strong expertise in automation frameworks (Selenium, Playwright, Cypress, PyTest, Robot, etc.) Hands-on experience with API testing (Postman, RestAssured, etc.) Strong understanding of CI/CD pipelines and test deployment workflows Experience in automating different aspects of SDLC, including integration, regression, performance, and data validation Strong scripting/programming skills (Python/Java/JavaScript or similar) Experience manipulating large datasets for validation and workflow testing Solid understanding of SDLC, STLC, and modern QA methodologies Excellent debugging, analytical, and communication skills