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Cognizant
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Gen AI QA Engineer

Gen AI QA Engineer

Cognizant

4 - 9 years

15 - 27 Lacs

chennai coimbatore

Posted:-1 days ago| Platform:

Apply

Skills Required

java generative ai api python

Work Mode

Hybrid

Job Type

Full Time

Job Description

We are seeking a talented and detail-oriented GenAI QA Engineer to ensure the quality, reliability, and performance of our generative AI applications, including RAG (Retrieval Augmented Generation) systems, chatbots, and AI agents. This role requires expertise in both manual and automated testing, with a strong focus on validating AI-specific behaviors and outputs.

Key Responsibilities

Test Strategy & Planning:
Design, develop, and execute comprehensive test plans and scenarios specifically for GenAI and LLM-based applications.
LLM Output Validation:
Validate LLM-generated responses against defined acceptance criteria, focusing on metrics like
faithfulness, precision, recall, coherence, and relevance
to minimize hallucinations.
Prompt Engineering Testing:
Design and implement test cases for prompt engineering pipelines, system prompts, and retrieval prompts, ensuring guardrails are effective and outputs are grounded in truth.
Automation Frameworks:
Develop and maintain robust automated test scripts using languages like
Python
or
Java
and frameworks such as Selenium, Pytest, or REST Assured.
API Testing:
Conduct rigorous testing of REST APIs and web services using tools like Postman or ReadyAPI to ensure seamless integration between the application components and AI models.
Data Quality Testing:
Perform data quality testing for RAG databases and vector databases (e.g., Pinecone, Chroma) to ensure relevant and high-quality data retrieval.
CI/CD Integration:
Integrate AI-specific evaluations and automation scripts into CI/CD pipelines (e.g., Jenkins, Azure DevOps) to enable continuous testing and delivery.
Defect Management:
Proactively identify, document, and analyze defects, collaborating with data science and development teams to resolve issues and improve model performance.
Mentorship & Best Practices:
Stay abreast of the latest advancements in AI testing and mentor junior QA peers on GenAI testing methodologies.

Required Skills & Qualifications

Experience:
Proven experience in software testing, QA, or SDET roles, with specific exposure to AI/ML or GenAI applications.
Programming Proficiency:
Strong proficiency in
Python
is typically a must-have, with knowledge of Java or JavaScript also highly valued for test automation.
QA Methodologies:
Excellent understanding of software QA methodologies, tools (JIRA, Azure DevOps), and processes within Agile/Scrum frameworks.
AI Knowledge:
Familiarity with LLM concepts, NLP (Natural Language Processing), and exposure to major models (e.g., OpenAI's GPT, Google's Gemini, Llama).
Testing Tools:
Hands-on experience with test automation tools (Selenium, Cypress) and API testing tools (Postman, REST Assured).
Evaluation Frameworks:
Knowledge or experience with AI/RAG evaluation frameworks like Ragas or Deep Eval is highly beneficial.

Preferred Qualifications:

4-10 years in proficiency in Java/Python Testing(Mandatory)
Expert in Selenium Automation(Mandatory)
Strong in API Automation(Mandatory)
Minimum 1 year in Generative AI(Mandatory)
Proficiency in Prompt Engineering
Knowledge of Natural Language Processing (NLP) and NLP Algorithms
Familiarity with Vector Databases, Azure Cloud

Location

Date of Interview-06/12/2025

Mode of Interview-Face to Face Interview

Note: Please do not apply if you are not available to attend the F2F interview and if you do not have the above skills.

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Gen AI QA Engineer

Experience & Salary

Skills Required

Work Mode

Job Type

Job Description

Key Responsibilities

Test Strategy & Planning:

LLM Output Validation:

faithfulness, precision, recall, coherence, and relevance

Prompt Engineering Testing:

Automation Frameworks:

Python

Java

API Testing:

Data Quality Testing:

CI/CD Integration:

Defect Management:

Mentorship & Best Practices:

Required Skills & Qualifications

Experience:

Programming Proficiency:

Python

QA Methodologies:

AI Knowledge: