Job Overview

Cognizant is hiring a Junior SDET for an AI Quality Engineering role focused on Python, test automation, and emerging artificial intelligence applications. The position is designed for professionals with 2 to 3 years of experience in software testing and quality engineering who want to expand their skills into AI and Generative AI testing.

The role combines traditional software quality practices with testing approaches for AI-powered applications, including chatbots, copilots, conversational systems, and intelligent automation solutions. You will contribute to automation frameworks, functional and API testing, regression coverage, and AI-specific quality validation. The position provides an opportunity to work with development, product, and quality engineering teams while helping improve the reliability of evolving software products.

Key Responsibilities

• Design, develop, maintain, and improve automated testing frameworks and reusable testing utilities using Python.
• Create and execute functional, integration, regression, and API tests for web and mobile applications.
• Test AI-powered applications, chatbots, copilots, and conversational experiences.
• Develop practical test scenarios for prompt validation, response evaluation, and AI workflow behavior.
• Assess AI outputs for quality and identify issues such as hallucinations or unexpected model behavior.
• Support testing activities across the software development lifecycle and contribute to continuous testing initiatives.
• Work with developers, product owners, and quality engineering professionals to investigate defects and improve release quality.
• Troubleshoot test failures and application issues using structured debugging and analytical methods.
• Contribute to automation strategy and identify opportunities to improve test coverage, efficiency, and maintainability.
• Participate in quality improvement activities for AI-enabled software and intelligent automation solutions.

Required Skills

Candidates should have 2 to 3 years of experience in software testing or quality engineering and strong practical programming ability in Python. Hands-on experience creating or maintaining automated tests for web, mobile, or API-based applications is required.

A good understanding of software testing methodologies, SDLC concepts, QA practices, and test scripting is important. Candidates should be comfortable analyzing failures, identifying defects, debugging issues, and communicating findings to other members of the engineering team.

The role also requires strong analytical and problem-solving ability. Because the position involves emerging AI technologies, candidates should be willing to learn unfamiliar concepts and adapt their testing approach as products and AI capabilities evolve.

Preferred Skills

Exposure to Large Language Models and Generative AI is valuable. Familiarity with Prompt Engineering, AI Copilot testing, AI agents, agentic workflows, automation agents, or chatbot testing can help candidates stand out.

Knowledge of AI-specific testing concepts is also preferred, including prompt validation, AI evaluations, hallucination testing, model evaluation, AI security testing, and output quality assessment.

Familiarity with cloud platforms and CI/CD practices is an additional advantage, although the job description presents these as preferred rather than mandatory skills.

Education

The provided job description does not specify a required degree or formal educational qualification. Candidates should refer to the official Cognizant posting for any additional education requirements that may be applied during the hiring process.

Experience

This is a junior-level SDET opportunity requiring 2 to 3 years of professional experience in Software Testing and Quality Engineering. The experience should include practical exposure to automation testing and Python programming.

Required Technologies

• Python
• Test Automation
• API Testing
• Web Testing
• Mobile Testing

Preferred Technologies and Concepts

• Large Language Models (LLMs)
• Generative AI
• Prompt Engineering
• AI Copilot Testing
• AI Agents
• Agentic Workflows
• Automation Agents
• Chatbot Testing
• AI Evals
• AI Security Testing
• Cloud Platforms
• CI/CD

Soft Skills

A strong learning mindset is important for this role because AI Quality Engineering is an evolving area. Candidates should be curious about new AI technologies and willing to experiment with different approaches to testing.

Ownership and collaboration are also emphasized. The successful candidate should be able to take responsibility for assigned quality tasks, communicate clearly with developers and product owners, and contribute constructively to team decisions.

Strong analytical thinking, debugging ability, problem-solving skills, and communication are important for understanding failures and explaining quality risks in a clear manner.

Benefits of Working in this Role

This role provides an opportunity to build practical experience at the intersection of software testing, automation, Python development, and AI quality engineering. Engineers can gain exposure to testing AI-powered applications, copilots, conversational systems, and intelligent automation workflows.

The position can also help experienced testers develop skills in emerging areas such as AI evaluation, prompt validation, hallucination testing, model behavior analysis, and AI security testing.

Work Mode

The job listing identifies the work model as Hybrid. However, the job description separately specifies Noida as the role location. Candidates should verify the current working arrangement and office expectations with Cognizant during the application process.

Location

The job description identifies Noida as the position location, while the Cognizant listing displays Chennai and India in its location information. Candidates should verify the applicable work location before applying because the role title specifically references Noida.

Who Should Apply

This opportunity is suitable for SDET professionals, QA Engineers, Software Test Engineers, Automation Test Engineers, and Quality Engineering professionals with 2 to 3 years of relevant experience.

It is particularly relevant to candidates who already know Python and have practical experience with automated testing for web, mobile, or API applications. Testers interested in moving toward AI Quality Engineering should consider this role if they are comfortable learning LLMs, Generative AI, prompt testing, AI evaluation, and agent-based application concepts.

Candidates who enjoy debugging, building reusable automation, investigating unexpected application behavior, and collaborating with software development teams may be a strong fit.

Career Growth

The role can help a Junior SDET expand from conventional automation testing into specialized AI Quality Engineering. With continued experience, professionals can develop deeper expertise in test automation architecture, Python-based frameworks, API testing, AI evaluation, model behavior testing, and quality strategy.

Experience with AI applications can also provide a foundation for future roles involving AI testing, SDET engineering, Quality Engineering leadership, automation architecture, or specialized testing of intelligent systems.

Application Advice

Highlight your Python programming experience and describe the automation frameworks, test scripts, APIs, web applications, mobile applications, or services you have tested. Explain your contribution rather than only listing tools.

If you have worked with LLMs, Generative AI, chatbots, copilots, prompt engineering, AI agents, or AI evaluation, include those projects clearly. Examples involving hallucination detection, response quality, prompt validation, or model behavior testing are especially relevant.

Also mention experience with SDLC, QA methodologies, defect analysis, regression testing, API testing, and CI/CD or cloud environments where applicable. Demonstrate your ability to learn quickly, troubleshoot issues, communicate findings, and take ownership of quality outcomes.