QA Automation Intern

Role Overview

The QA Automation Intern will support the development and testing of next-generation AI-driven products. This role focuses on designing automated test scripts, validating AI-generated outputs, and ensuring the reliability of automated workflows.

You will collaborate closely with engineering and AI teams to test integrations, validate complex logic, and maintain high-quality standards across software systems. The role goes beyond manual testing and emphasizes automation, problem solving, and evaluation of AI model outputs.

Key Responsibilities

Automation Development

Design and maintain automated test scripts for web applications.
Work with automation frameworks such as Playwright, Selenium, or Cypress.
Identify and troubleshoot flaky or unstable automated tests.
Ensure automation frameworks are reliable and maintainable.

LLM Evaluation

Develop strategies to evaluate responses generated by AI systems.
Detect issues such as hallucinations, prompt injection attempts, and formatting errors.
Create programmatic validation methods for Large Language Model outputs.

Workflow Testing

Test complex automation workflows built with platforms such as n8n, Zapier, or Make.com.
Validate data flow and integration between multiple APIs and services.
Ensure automation logic works correctly across edge cases and complex scenarios.

API Testing

Test backend APIs using tools such as Postman or Python scripts.
Validate request and response structures and ensure reliable integrations.
Monitor API performance and reliability.

Problem Solving

Perform root cause analysis for automation failures.
Identify performance bottlenecks and workflow failures.
Suggest improvements to enhance testing processes and automation reliability.

Technical Requirements

Strong programming foundation in Python or JavaScript.
Ability to map complex workflows and identify potential points of failure in automation pipelines.
Strong logical thinking and analytical problem-solving skills.
Basic understanding of Large Language Models (LLMs) and how they generate outputs.
Familiarity with evaluating responses from models such as GPT, Claude, or Gemini.

Education

Recent graduate with a B.E. or B.Tech degree in Computer Science, Information Technology, or a related field.

What You Will Gain

Hands-on experience in AI product testing and automation.
Exposure to LLM evaluation techniques and workflow automation platforms.
Opportunity to work with modern AI-driven software systems.
Mentorship from experienced engineers and AI professionals.