| Location | Atlanta, GA |
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Senior GCP DevOps Engineer
Hybrid in Georgia, & 3 others
Google Cloud Platform
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We are seeking a talented Senior GCP DevOps Engineer to assist clients with deploying Google Cloud Platform products. In this position, you will provide architecture guidance, data migration, troubleshooting, and monitoring while making sure best practices are upheld. If you are ready to make an impact, we encourage you to apply!
We would like to inform you that this role is primarily offered under a standard employment contract, in accordance with applicable labor regulations.
Responsibilities
Define technical requirements and project scope
Maintain active communication with customers to ensure project alignment
Facilitate the adaptation of customer applications to a Cloud-Native approach
Apply DevOps practices, including CI/CD and Infrastructure as Code (IaaC)
Architect and optimize cloud applications for scalability, including CDN, caching, compute optimizations, and load balancing setups
Help deploy and configure GCP services such as identity management, network architecture, application security, and billing
Record technical decisions, designs, and processes for future reference
Track and troubleshoot cloud applications, including network connectivity and cluster performance
Exchange knowledge and participate in training sessions to grow team expertise
Requirements
3+ years of experience in DevOps, Cloud Engineering, or related roles
Qualifications in GCP services such as Google Kubernetes Engine (GKE), CloudBuild, Secret Management, and Container Registry
Background in ensuring high availability, scalability, and security for Kubernetes clusters and applications
Proficiency in Version Control systems, including GitHub
Expertise in CI/CD tools such as GitHub Actions and/or Jenkins
Skills in building and managing Dockerfiles and Kubernetes YAML configurations
Knowledge of infrastructure automation and configuration management tools like Terraform or Ansible
Capability to troubleshoot and resolve issues related to Kubernetes clusters and network connectivity
Familiarity with diagnosing and debugging Python-based applications
Background in enterprise AI integration using AWS Bedrock, Google Vertex AI, and Azure AI Services
Expertise in designing, building, and operating AI agents and agentic AI frameworks
Solid knowledge of Retrieval-Augmented Generation (RAG) architectures and implementation
Showcase of AI-assisted development tools, such as Cursor, Claude Code, Trae, OpenCode, Antigravity, or similar
Understanding of modern Generative AI technologies, LLMs, and enterprise AI solution design
Strong English communication skills (B2 level or higher)