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# Sr. DevOps Engineer

- **Company:** Advanced
- **Location:** Sandy Springs, GA, United States (Remote available)
- **Experience:** Expert
- **Contract:** Permanent contract
- **Skills:** Application Programming Interfaces (APIs), Artificial Intelligence, Amazon Web Services, Microsoft Azure, Bash Shell, Cloud Computing, Continuous Delivery, Continuous Integration, DevOps, Github, Python (Programming Language), Automation of Marketing, Microsoft Copilot, Datadog, Scripting, GitHub Copilot, Delivery Pipeline, Claude Code, Zapier, AI Coding Agents, Agentic-AI, Gitlab-ci, Low-code, Nintex, Terraform, Jenkins, Vulnerability Analysis
- **Published:** October 29, 2026
- **Apply:** https://www.careerbuilder.com/job-details/sr-devops-engineer-atlanta-ga--faa67fe5-5d31-4444-8d87-e18e7fe44086

## About the Role

DevOps, Reporting Dashboards, Cloud Computing, Automation, Artificial Intelligence (AI), Machine Tool, DevOps, Continuous Integration, Continuous Deployment/Delivery, Application Programming Interface (API), Required:

 * 4 7+ years in DevOps, SRE, or cloud infrastructure engineering roles
 * Strong hands-on experience with a major cloud provider (AWS, Azure); AWS GovCloud experience is a plus
 * Proficiency with infrastructure-as-code (Terraform strongly preferred)
 * Solid scripting/automation skills (Python, Bash, or similar)
 * Experience with CI/CD tooling (GitLab CI, GitHub Actions, Jenkins, or similar)
 * Comfort working in regulated/compliance-heavy environments (FedRAMP, IL5, SOC 2, or similar)
 * Genuine curiosity about AI/automation tooling and a track record of adopting new tools to improve workflows

Nice to Have:

 * Experience with low-code automation platforms (n8n, Zapier)
 * Familiarity with AI coding agents (Claude Code, GitHub Copilot, Codex) in a professional engineering setting
 * Experience supporting federal clients or federal compliance frameworks (FedRAMP, IL5)
 * Datadog or equivalent observability platform experience
 * Container hardening / security scanning experience (e.g., RapidFort)

Additional Information:

This position requires access to information that is controlled by the Export Administration Regulations ( EAR ). A candidate must qualify as a U.S. Person or be otherwise eligible to access EAR covered materials through an EAR exception or license. A "U.S. Person" as defined by the EAR includes a U.S. Citizen, U.S. national, lawful permanent resident, refugee, or asylee.

As the Company is a partner with the United States government, this position may require access to sensitive government information. Accordingly, candidates must be capable of passing an SF-85 background check and obtaining public trust clearance if required.

## Description

We're looking for a mid-to-senior DevOps Engineer who thrives at the intersection of infrastructure automation and applied AI tooling. You'll help us build and scale the systems that keep our cloud infrastructure secure, compliant, and efficient while also driving adoption of AI-assisted engineering workflows (agentic coding tools, automation pipelines, and AI-powered operational dashboards) across the team.

This isn't a "keep the lights on" DevOps Engineer role. You'll be expected to actively look for ways to automate toil out of infrastructure, security, and compliance work and to bring modern AI tooling into that process where it adds real leverage.

Location

 * Atlanta / Remote

What You'll Do

 * Design, build, and maintain infrastructure-as-code (Terraform) across multi-account cloud environments, with an eye toward cost efficiency, security, and compliance (FedRAMP/GovCloud experience a strong plus)
 * Build and maintain CI/CD pipelines supporting frequent, safe deployments
 * Develop automation workflows (e.g., n8n, Zapier, custom scripts/APIs) that reduce manual operational and compliance work
 * Integrate AI coding assistants and agentic tools (Claude Code, Copilot, or similar) into engineering workflows, and help establish governance/cost practices for AI tooling adoption org-wide
 * Monitor infrastructure health and security posture using tools like Datadog, building dashboards and alerting that surfaces real signal, end-to-end visibility, actionable alerts, dependency monitoring, and automated remediation.
 * Continuously identify opportunities to eliminate repetitive work through scripting, IaC, or AI-assisted tooling