Cloud Platform Engineering Intern

Job Title

Cloud Platform Engineering Intern

Job Description

About People Inc:
People Inc. is America’s largest digital and print publisher. Our 40+ iconic and fast-growing brands harness the best intent-driven content, the fastest sites, and the fewest ads to help nearly 200 million people every month, including 95 percent of US women, make decisions, take action, and find inspiration. People Inc. brands include PEOPLE, Better Homes & Gardens, Verywell, FOOD & WINE, The Spruce, Allrecipes, Byrdie, REAL SIMPLE, Investopedia, Southern Living and more.

About The Role:

We are seeking a Cloud Platform Engineering Intern to help build, automate, and validate infrastructure across Amazon Web Services (AWS), Google Cloud Platform (GCP), and Kubernetes environments.

This role is ideal for someone interested in cloud engineering, platform automation, and the emerging use of AI in infrastructure operations. The intern will work alongside Cloud Platform engineers to build tools that interact with infrastructure, collect and analyze operational data, validate configurations, and produce actionable reports.

The position will have a strong focus on Kubernetes, Infrastructure as Code, Configuration as Code, and AI-assisted infrastructure management. The intern will gain practical experience working with production-oriented cloud platforms while learning how to build automation that is secure, observable, repeatable, and safe to operate.

Responsibilities:

• Develop tools and scripts that query, inspect, and report on AWS, GCP, and Kubernetes resources.

• Build infrastructure inventory, configuration validation, compliance reporting, and operational health-check utilities.

• Help automate cloud and Kubernetes infrastructure using Infrastructure as Code tools such as Terraform.

• Contribute to Configuration as Code using tools such as Helm, Kustomize, Ansible, and declarative YAML.

• Develop AI-assisted workflows for infrastructure analysis, troubleshooting, configuration generation, and validation.

• Implement safeguards for AI-enabled infrastructure workflows, including schema validation, policy checks, dry-run capabilities, approval gates, and human review.

• Integrate infrastructure tools with cloud APIs, Kubernetes APIs, CI/CD pipelines, Git repositories, and observability platforms.

• Assist with validating Kubernetes manifests, Terraform plans, deployment configurations, and cloud resource settings.

• Build reports and dashboards that identify configuration drift, resource usage, security risks, operational issues, and optimization opportunities.

• Write unit and integration tests for infrastructure automation and validation tools.

• Document tools, workflows, configuration standards, and operational procedures.

• Participate in code reviews, technical design discussions, and platform engineering planning.

• Work with engineers to investigate infrastructure issues and identify opportunities for automation.

Required Qualifications:

• Currently pursuing a degree or equivalent training in Computer Science, Software Engineering, Information Technology, Cybersecurity, or a related field.

• Foundational programming or scripting experience in one or more languages such as Python, Go, JavaScript/TypeScript, or Bash.

• Basic understanding of Linux, networking, APIs, source control, and software development practices.

• Familiarity with containers and an interest in Kubernetes and cloud infrastructure.

• Familiarity with Git and collaborative development workflows.

• Strong analytical and problem-solving skills.

• Ability to learn unfamiliar technologies and ask effective technical questions.

• Clear written and verbal communication skills.

• Interest in automation, developer platforms, and reliable infrastructure operations.

Preferred Qualifications:

Experience with any of the following is helpful but not required:

• AWS or Google Cloud Platform.

• Kubernetes, Docker, Helm, or Kustomize.

• Terraform or another Infrastructure as Code framework.

• Ansible or other configuration-management tools.

• CI/CD platforms such as GitHub Actions, Jenkins, Argo CD, or Argo Workflows

• REST APIs, cloud SDKs, or Kubernetes client libraries.

• Data collection, reporting, dashboards, or observability tools.

• Large language models, AI agents, tool-calling systems, or Model Context Protocol (MCP).

• Automated testing, policy-as-code, or configuration validation.

• Cloud security concepts such as IAM, workload identity, secrets management, and least-privilege access.

* This People Inc. Canada internship is scheduled to end in May 2027.

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