The Role
Develop and maintain automated tests for web, API, and backend systems; execute regression, integration, and end-to-end testing; integrate tests into CI/CD pipelines; validate APIs and data workflows; debug defects; improve automation coverage and reliability; and support performance testing and quality improvements for AI/ML platforms.
Summary Generated by Built In
About GoML
Role Overview
What You’ll Do (Key Responsibilities)Initial Phase (0–30 Days)
What You Bring (Skills & Qualifications)Must-Have
Why Work With Us?
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. Our mission is to bridge state-of-the-art AI research with real-world enterprise applications—enabling organizations to innovate faster, make smarter decisions, and scale AI solutions seamlessly.
Role Overview
We’re looking for a QA Automation Engineer with strong hands-on experience in test automation, API testing, and CI/CD integration. In this role, you’ll work closely with engineering, data, and DevOps teams to ensure our AI-powered platforms are reliable, scalable, and production-ready.
If you enjoy building robust automation frameworks, validating complex data workflows, and continuously improving product quality, this role is for you.
- Understand GoML’s AI/ML & GenAI products, workflows, and QA practices
- Review existing automation frameworks, test coverage, and pipelines
- Collaborate with developers to understand product functionality and quality expectations
- Develop and maintain automated test cases for web, API, and backend systems
- Execute regression, integration, and end-to-end tests
- Contribute to CI/CD-integrated test pipelines
- Perform API and data validation testing
- Identify defects, debug issues, and work with teams to ensure quick resolution
- Improve automation coverage and test reliability
- Assist in defining QA best practices and documentation
- Support performance and scalability testing efforts
- Collaborate on quality improvements for AI/ML-driven features
- 2+ years of experience in QA Automation or Software Testing
- Hands-on experience with automation tools such as Selenium, Playwright, Cypress, PyTest, or similar
- Strong experience in API testing (Postman, RestAssured, etc.)
- Working knowledge of CI/CD pipelines (GitHub Actions, GitLab, Jenkins, etc.)
- Experience with regression, integration, and end-to-end testing
- Proficiency in Python, Java, or JavaScript
- Good understanding of SDLC, STLC, and Agile methodologies
- Strong analytical, debugging, and communication skills
- Exposure to AI/ML systems, data pipelines, or analytics platforms
- Experience with performance testing tools (JMeter, Locust, k6)
- Familiarity with Docker and cloud platforms (AWS/GCP/Azure)
- Interest in AI-assisted or data-driven testing approaches
- Remote-first culture with offices in Coimbatore for collaboration
- Opportunity to work on cutting-edge AI/ML & GenAI platforms
- Learn from experienced leaders and work on real-world enterprise problems
- Competitive compensation, strong learning curve, and growth opportunities
Skills Required
- 2+ years of experience in QA automation or software testing
- Hands-on experience with automation tools such as Selenium, Playwright, Cypress, PyTest, or similar
- Strong experience in API testing using tools such as Postman or RestAssured
- Working knowledge of CI/CD pipelines, including GitHub Actions, GitLab, or Jenkins
- Experience with regression, integration, and end-to-end testing
- Proficiency in Python, Java, or JavaScript
- Understanding of SDLC, STLC, and Agile methodologies
- Strong analytical, debugging, and communication skills
- Exposure to AI/ML systems, data pipelines, or analytics platforms
- Experience with performance testing tools such as JMeter, Locust, or k6
- Familiarity with Docker and cloud platforms such as AWS, GCP, or Azure
- Interest in AI-assisted or data-driven testing approaches
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The Company
What We Do
Neuralgo.ai is an enterprise AI and data-science company building LLM-powered platforms that help users move from business problem statements to machine-learning solutions. Its offerings span data engineering, MLOps, and LLM applications, providing productized outcomes across the machine-learning lifecycle. The company’s mission is to democratize data science with AI and help organizations accelerate their machine-learning initiatives.








