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# Engineer, DevOps

- **Company:** The Stagwell Group
- **Location:** United States
- **Experience:** Expert
- **Salary:** $110,000.0 - $150,000.0
- **Contract:** Permanent contract
- **Skills:** Artificial Intelligence, Amazon Web Services, Amazon Cloudfront, Microsoft Azure, Bash Shell, Cloud Engineering, System Configuration, Software Debugging, Programming Tools, Fault Tolerance, Github, Python (Programming Language), Key Management, Linux System Administration, Nginx, Systems Development Life Cycle, Ansible, Next.js, SonarQube, Web Applications, Datadog, Data Logging, Scripting, Load Balancing, Cloud Platform System, Sonatype, AWS Lambda, Git, Cloudformation, Infrastructure Automation Frameworks, Deployment Automation, Hashicorp, Bitbucket, Cloudwatch, Terraform, New Relic (SaaS), Devsecops, Serverless Computing, Docker, Jenkins
- **Published:** July 7, 2026
- **Apply:** https://www.codeandtheory.com/careers/8594730002?gh_jid=8594730002

## About the Role

* Extensive experience provisioning and managing cloud infrastructure on AWS, GCP, and/or Azure
 * Strong proficiency with IaC tools - Terraform, AWS CloudFormation, and Ansible
 * Experience with CI/CD pipelines in GitHub Actions, Bitbucket Pipelines, or Jenkins
 * Deep expertise with Docker and Kubernetes
 * Experience designing high-availability, fault-tolerant architectures
 * Solid understanding of deployment strategies: blue-green, canary releases, and feature flags
 * Experience with serverless architectures - AWS Lambda, GCP Cloud Functions, or Azure Functions
 * Familiarity with edge platforms and CDNs such as Fastly and AWS CloudFront
 * Experience with developer platforms such as Vercel, Netlify, and WP Engine
 * Deep understanding of security best practices and hands-on DevSecOps experience
 * Experience with Snyk, SonarQube, AWS Secrets Manager, and HashiCorp Vault
 * Experience with observability platforms - New Relic, Datadog, or AWS CloudWatch
 * Solid Linux administration and experience configuring NGINX, Traefik, and load balancers
 * Proficiency scripting in bash and Python for automation and internal tooling
 * Deep understanding of networking, cloud architectures, and web application design
 * Experience with Git and managed platforms such as GitHub, Bitbucket, and Azure DevOps
 * Experience implementing cloud cost optimization and FinOps practices
 * Strong communication skills - able to discuss complex technical topics and author clear documentation
 * Comfortable leveraging AI-enabled development tools and workflows to accelerate engineering, automation, debugging, and operational tasks
 * Experience orchestrating multi-step AI or agent-driven workflows, including selecting appropriate models, tools, and execution patterns for different use cases
 * Strong judgment reviewing and hardening AI-assisted output for security, scalability, maintainability, and architectural fit
 * Experience building or maintaining prompts, evaluation frameworks, documentation, or operational context systems that improve engineering velocity and reliability
 * Familiarity with automated evaluation and feedback loops for AI-enabled systems and workflows

NICE TO HAVE

 * Experience in agency, consultancy, or enterprise SaaS organizations
 * AWS, GCP, or Azure cloud certifications

## Description

* Design and maintain scalable cloud infrastructure across AWS, GCP, and Azure with a focus on high availability and operational excellence
 * Build and evolve CI/CD pipelines for fast, safe software delivery - from commit to production
 * Embed DevSecOps principles across the pipeline: security scanning, secrets management, and compliance by default
 * Lead IaC practices with Terraform, CloudFormation, and Ansible - keeping environments reproducible and auditable
 * Own observability: monitoring, alerting, logging, and tracing across all systems
 * Drive cloud cost optimization, identifying inefficiencies and right-sizing resources proactively
 * Partner with engineering teams to improve developer experience and remove friction from the SDLC
 * Maintain architecture documentation, runbooks, and post-mortems to support a culture of continuous improvement


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