Cloud Engineer

Job not on LinkedIn

🔥 18 minutes ago

🇺🇸 United States – Remote

💵 $80k - $100k / year

⏰ Full Time

🟡 Mid-level

🟠 Senior

☁️ Cloud Engineer

👻 Ghost score 0%

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NeuroHire

WebsiteLinkedInAll Job Openings

2 - 10 employees

Founded 2025

☁️ SaaS

👥 HR Tech

🎯 Recruiter

SaaS • HR Tech • Recruitment

NeuroHire is an all-in-one SaaS "Career Operating System" that combines AI-driven automation with human career specialists to help IT professionals—especially international students and visa-dependent candidates—navigate the U. S. tech job market. The platform automates job discovery, resume and ATS optimization, large-scale application management, and company-specific interview preparation while human experts verify submissions, provide cultural and visa-aware guidance, and deliver coaching. NeuroHire positions itself as a human+AI symbiosis validated in a pilot program to deliver interview invites and job offers for IT candidates seeking U. S. roles.

📋 Description

• Assist in configuring, deploying, and maintaining cloud infrastructure and services. • Support cloud environments using AWS, Microsoft Azure, or Google Cloud Platform (GCP). • Monitor cloud resources, system performance, availability, and resource utilization. • Assist with infrastructure provisioning, configuration management, and routine maintenance. • Support the deployment and management of cloud-hosted applications and services. • Work with Linux or Windows operating systems to troubleshoot technical issues. • Assist in implementing cloud security best practices, access controls, and resource permissions. • Use Python, Bash, or PowerShell to automate routine operational tasks. • Support containerization and deployment workflows using Docker and related tools. • Collaborate with software development and operations teams to improve deployment reliability. • Assist with troubleshooting cloud infrastructure, connectivity, performance, and configuration issues. • Maintain technical documentation for cloud resources, deployment procedures, and operational processes. • Learn and apply Infrastructure as Code (IaC) tools and modern cloud engineering practices.

🎯 Requirements

• Master's degree in Computer Science, Information Technology, Computer Engineering, Software Engineering, or a related technical field. • 0–1 year of experience in Cloud Engineering, Cloud Computing, DevOps, Systems Administration, or a related technical role. • Strong understanding of cloud computing fundamentals, including compute, storage, networking, and virtualization. • Familiarity with at least one cloud platform: AWS, Microsoft Azure, or Google Cloud Platform (GCP). • Basic knowledge of Linux or Windows operating systems and command-line tools. • Familiarity with networking fundamentals, including DNS, IP addressing, HTTP/HTTPS, and firewalls. • Basic scripting knowledge in Python, Bash, or PowerShell. • Understanding of identity and access management (IAM), permissions, and cloud security fundamentals. • Familiarity with Git and GitHub for version control. • Basic understanding of CI/CD concepts and software deployment workflows. • Familiarity with Docker, containers, or Kubernetes is an advantage. • Awareness of Infrastructure as Code tools such as Terraform or AWS CloudFormation is a plus. • Strong troubleshooting, analytical thinking, and problem-solving abilities. • Ability to learn new technologies and adapt to evolving technical requirements. • Strong communication, teamwork, and collaboration skills.

🏖️ Benefits

• Opportunity to contribute to an innovative, AI-powered technology company. • Hands-on exposure to cloud infrastructure and modern deployment technologies. • Opportunities to develop practical skills in cloud computing, automation, and infrastructure management. • Collaborative environment that encourages continuous learning and knowledge sharing. • Opportunities for professional development and technical growth. • Exposure to cloud platforms, infrastructure monitoring, and deployment best practices. • Opportunity to contribute to improving system reliability, scalability, and operational efficiency.

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