Cloud Engineer Internship

Roles & Responsibilities

• Assist in designing, deploying, configuring, and maintaining cloud infrastructure using AWS, Google Cloud Platform (GCP), or Microsoft Azure.
• Explore and develop AI agents capable of automating cloud operations, executing workflows, and supporting intelligent decision-making.
• Build automation solutions using Agentic AI, LLMs, APIs, and Python to simplify infrastructure management.
• Support application deployment, CI/CD pipelines, containerization, and infrastructure automation.
• Work with Google Cloud technologies, AI services, cloud-native tools, and emerging AI-powered development platforms.
• Assist in monitoring cloud resources, analyzing performance, troubleshooting issues, and optimizing infrastructure.
• Explore tools such as Terraform, Docker, Kubernetes, and cloud automation frameworks.
• Experiment with emerging technologies in Generative AI, Agentic AI, autonomous workflows, and intelligent cloud computing.
• Document technical implementations, collaborate with engineering teams, and contribute to real-world projects.

Requirements

• Currently pursuing or recently completed a degree in Computer Science, Information Technology, Cloud Computing, or a related field.
• Basic understanding of Cloud Computing concepts and cloud infrastructure.
• Familiarity with at least one cloud platform: AWS, Google Cloud (GCP), or Microsoft Azure.
• Basic programming knowledge in Python, Java, or JavaScript.
• Understanding of APIs, networking, Linux, and operating system fundamentals.
• Interest in Generative AI, Large Language Models (LLMs), and Agentic AI.
• Familiarity with AI agents, LangChain, LangGraph, CrewAI, or similar frameworks is an advantage.
• Basic knowledge of Docker, Kubernetes, Git, CI/CD, or Terraform is a plus.
• Strong problem-solving, analytical thinking, and debugging skills.
• Willingness to learn, experiment, innovate, and work with emerging technologies.

What You Will Gain

• Hands-on exposure to real-world cloud engineering projects.
• Practical experience with Agentic AI and AI-powered automation.
• Opportunity to explore Google Cloud, AWS, and modern cloud technologies.
• Experience building intelligent automation workflows and cloud-native applications.
• Exposure to industry-relevant tools, frameworks, and engineering practices.
• Opportunity to strengthen your technical portfolio and problem-solving skills.