AI & Automation Validation Engineer

Job Requirements

What You'll Do

- Design, develop, and maintain automated test and validation solutions for complex software systems.
- Build automated tests for REST APIs, integrations, databases, and end-to-end workflows.
- Validate software across hybrid and heterogeneous technology environments.
- Integrate automated tests into CI/CD pipelines to enable continuous quality feedback.
- Define and improve test strategies, coverage, traceability, and defect-management practices.
- Validate AI-assisted, LLM-based, and agent-driven workflows for reliability, robustness, and expected behavior.
- Explore Generative AI and AI-assisted techniques for test generation, optimization, and analysis.
- Collaborate across development, architecture, DevOps, product, and other functions to embed quality throughout the software lifecycle.

Work Experience

What We're Looking For

- Experience: 3–6 years of experience in Software Testing and Quality Assurance with strong experience in software testing, validation, and test automation.
- Education: B.E. / B. Tech / M.Sc. / MCA in Computer Science, Information Technology, or equivalent.
- API Testing: Hands-on experience with RESTful API testing using Postman, Swagger/OpenAPI, or similar tools.  Data Validation: Experience with database and data validation.
- Hybrid Environments: Experience testing solutions involving multiple technologies, services, components, and interfaces.
- CI/CD & Source Control: Hands-on experience with Git and CI/CD tools such as Azure Pipelines, GitHub Actions, or equivalent.
- Quality Engineering: Good understanding of Agile, Scrum, TDD, BDD, and modern quality-engineering practices.
- AI Validation: Experience testing AI agents, LLM-based applications, or Generative AI solutions is considered an advantage.
- AI Evaluation: Familiarity with AI-agent orchestration frameworks and AI/LLM evaluation approaches is considered an advantage.
- Cloud & Containers: Experience with Azure, AWS, or GCP, as well as Docker and Kubernetes, is considered an advantage.
- Security Testing: Familiarity with DAST, security testing, and penetration-testing concepts is considered an advantage.
- Web Testing: Experience in functional, performance, and cross-browser testing of web applications is considered an advantage.
- Test Management: Experience with Azure DevOps, TFS, Jira, or equivalent test and defect-management tools.  Collaboration: Strong analytical, problem-solving, communication, and cross-functional collaboration skills.

What Defines Success

You bring automation first, quality-driven, and AI-aware mindset. You help engineering teams detect risks earlier, reduce repetitive manual validation, improve engineering efficiency, and deliver reliable, scalable, secure, and fit-for-purpose software solutions.