> Markdown version of [/jobs/ext/4484705-cloud-architect-in-united](https://www.wearedevelopers.com/jobs/ext/4484705-cloud-architect-in-united). Every page supports `.md` or `Accept: text/markdown`. Links point to the HTML versions so they work for humans too. Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Cloud Architect in United - **Company:** Energy Jobline - **Location:** Carbon, WV, United States (Remote available) - **Salary:** $132,000.0 - $165,000.0 - **Contract:** Permanent contract - **Skills:** Amazon Web Services, Batch Processing, Cloud Computing, Continuous Integration, DevOps, Github, Software Engineering, Deployment Automation, Terraform - **Published:** October 31, 2026 - **Apply:** https://www.energyjobline.com/job/cloud-architect-united-32119166 ## About the Role We're looking for someone who has engineered AWS, not just operated it - who has stood up Terraform from scratch, scripted and automated environments, and built the repeatability that a growing org depends on. Combined with the breadth to move across Cloud Ops, DevOps, and SRE, that's the profile. AWS production experience and practical Terraform experience are must-haves. A software engineering background is a strong signal, but not required., * A software engineering background - someone who has written and deployed code understands production decisions at a different level \n * Experience standing up or maturing an IaC practice - Terraform modules, state management, remote backends, GitHub-based workflows \n * Experience with performance management in production AWS environments - batch processing, throughput analysis, capacity planning \n * Hands-on CI/CD pipeline experience in AWS including deployment automation ## Description Three things need to be built: infrastructure as code - getting the AWS environment scripted in Terraform, version-controlled in GitHub, and consistently reproducible; performance visibility - monitoring and alerting that catches degradation before clients feel it; and structured deployment practices that are safe, documented, and don't depend on any one person being available. Once that foundation is in place, the work shifts toward automation and AI tooling.