Senior Google Cloud Platform DevOps Engineer

We are seeking a talented Senior Google Cloud Platform 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 Google Cloud Platform 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 Google Cloud Platform 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)