INTERNSHIP - AI for Software Testing
5 days ago
Goal:
We are looking for a motivated intern with a passion for exploring how AI can transform software development lifecycle.
You will work closely with our development and testing teams to:
• Experiment with cutting-edge AI tools,
• Apply them to test generation, improve automation, and reporting,
• Benchmark their impact on team performance
• Propose improvements for our processes.
This internship is hands-on: you'll shadow developers and testers, try out AI models, build agents based on real project context, and document results.
Key Responsibilities:
AI for Testing
- Build AI agents to generate unit tests, functional tests, and integration tests.
- Review AI-generated test cases with teams and evaluate accuracy, coverage, and maintainability and document results.
- Support the creation/integrate AI agents using MCP servers to improve development performance and software quality.
AI for Test Management
- Prototype AI agents to generate test plans and test cases from user stories, requirements, and architecture designs.
- Experiment with AI-assisted test uploads and management in Jira.
- Evaluate the acceptance test creation using AI agents.
Process Improvement
- Shadow development and QA teams to identify opportunities where AI can improve workflows (e.g., documentation, sprint summaries, reporting).
- Propose new ways to integrate AI into daily dev/test practices.
Research & Reporting
- Document experiments and evaluations in a clear, structured way.
- Provide comparative reports on AI tools, including metrics and team feedback.
- Present findings and recommendations to the wider team.
Tools & Technologies You'll Work With
- Programming: Python (main language), others like JavaScript, Java, .NET
- Testing: Robot Framework, unit/functional test frameworks, Postman.
- AI Tools: IDE plugins (VS Code, IntelliJ), AI models, cline, MCP servers.
- Collaboration: Jira, Confluence, GitLab.
Requirements
- Knowledge of AI (how things work - basics of machine learning, agents architecture, AI agentic, etc.)
- Understanding of Model Context Protocol (MCP)
- Hands-on experience with prompt engineering
- General knowledge of software engineering processes and practices
- Python coding experience
- Ability to read code in other programming languages such as JavaScript, Java, .NET
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