Cloud Engineer Internship

Skills this role screens for

About the role

Roles & Responsibilities • Cloud Infrastructure Management: Assist in designing, deploying, configuring, and maintaining cloud infrastructure using AWS, Google Cloud Platform (GCP), or Microsoft Azure. • Agentic AI Development: Explore and develop AI agents capable of automating cloud operations, executing workflows, and supporting intelligent decision-making. • AI-Powered Cloud Automation: Build automation solutions using Agentic AI, LLMs, APIs, and Python to simplify infrastructure management. • Cloud Deployment & DevOps: Support application deployment, CI/CD pipelines, containerization, and infrastructure automation. • Google Cloud & AI Ecosystem: Work with Google Cloud technologies, AI services, cloud-native tools, and emerging AI-powered development platforms. • Monitoring & Optimization: Assist in monitoring cloud resources, analyzing performance, troubleshooting issues, and optimizing infrastructure. • Infrastructure as Code (IaC): Explore tools such as Terraform, Docker, Kubernetes, and cloud automation frameworks. • Research & Innovation: Experiment with emerging technologies in Generative AI, Agentic AI, autonomous workflows, and intelligent cloud computing. • Documentation & Collaboration: 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. Good to Have Skills • Google Cloud Platform (GCP) and Google Cloud AI tools. • AWS cloud services and Azure fundamentals. • Agentic AI frameworks and multi-agent architectures. • Prompt Engineering and LLM integrations. • Python-based automation and API development. • DevOps, MLOps, and Cloud-Native Architecture. • Serverless Computing and Microservices. 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. Who Should Apply? • Students passionate about Cloud Engineering and Artificial Intelligence. • Aspiring Cloud Engineers, DevOps Engineers, and AI Engineers. • Beginners interested in Google Cloud, AWS, and Azure. • Developers excited about building autonomous AI agents. • Individuals who love experimenting with emerging technologies and solving real-world problems.