Opportunity brief
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.