Job Summary
We are seeking a
QA Engineer – AI
with
3–7 years of experience
to validate AI-powered applications, automation workflows, and intelligent systems. The ideal candidate should have strong expertise in manual and automation testing, API testing, and experience validating Generative AI/LLM-based applications. You will work closely with developers, AI engineers, and product teams to ensure the quality, reliability, and performance of AI solutions.
Key Responsibilities
- Design, develop, and execute comprehensive test plans, test cases, and test scenarios for AI-enabled applications.
- Perform functional, regression, integration, system, and end-to-end testing.
- Validate AI/LLM outputs for accuracy, consistency, hallucinations, bias, and edge cases.
- Develop and maintain automation frameworks for web and API testing.
- Perform REST API testing using Postman, Rest Assured, or similar tools.
- Create and execute test data strategies for AI model validation.
- Work with developers to identify, reproduce, and resolve defects.
- Validate prompt engineering scenarios and AI workflow integrations.
- Execute performance and reliability testing for AI-powered applications.
- Participate in Agile ceremonies, sprint planning, and defect triage meetings.
- Maintain test documentation, defect reports, and quality metrics using JIRA or Azure DevOps.
Mandatory Skills
- 3–7 years of experience in Software Testing/QA.
- Strong experience in Manual Testing and Automation Testing.
- Hands-on experience with
Selenium WebDriver
.
Java or Python
.
TestNG/JUnit
and automation frameworks.
API Testing
using Postman and/or Rest Assured.
SQL
and database validation.
Git
and version control.
Agile/Scrum
environments.
Generative AI
,
LLMs (ChatGPT, Gemini, Claude, etc.)
, prompt testing, or AI application validation.
- Experience with defect tracking tools such as
JIRA
.
Preferred Skills
- Experience testing applications built on
OpenAI, Azure OpenAI, Google Vertex AI, AWS Bedrock
, or similar AI platforms.
Python scripting
for test automation.
Playwright
or Cypress.
CI/CD
tools such as Jenkins, GitHub Actions, or Azure DevOps.
Docker
and basic Kubernetes concepts.
- Experience with performance testing tools such as JMeter.
- Familiarity with AI evaluation metrics, prompt engineering, Retrieval-Augmented Generation (RAG), and vector databases is an added advantage.
Qualifications
- Bachelor's degree in Computer Science, Information Technology, Engineering, or a related field.
Soft Skills
- Strong analytical and problem-solving abilities.
- Excellent communication and collaboration skills.
- Ability to work independently and in cross-functional teams.
- Attention to detail with a quality-first mindset.
- Eagerness to learn emerging AI technologies and testing methodologies.
