Lead GCP DevOps Engineer (AI-Enabled Platform)

About the job About The Role In this role, you will design and evolve cloud-native platforms on Google Cloud Platform, helping global organizations modernize infrastructure, accelerate software delivery, and improve operational resilience. Working within our Cloud and DevOps Practice, you'll collaborate with experienced engineers and architects to deliver secure, scalable, and AI-ready solutions while shaping engineering best practices across projects. Responsibilities Design, build, and operate scalable, secure, and reliable cloud infrastructure on Google Cloud Platform Lead or support migration initiatives from other clouds to GCP, ensuring service continuity, security, and cost optimization Build, maintain, and continuously improve CI/CD pipelines and deployment automation Develop and manage infrastructure using Terraform and Infrastructure as Code best practices Deploy, manage, and optimize containerized applications using Kubernetes and Docker Implement monitoring, logging, and alerting solutions to ensure platform reliability and performance Collaborate with software engineers, architects, and AI/ML teams to deliver cloud-native and AI-enabled solutions Support GPU-based infrastructure and AI workloads where applicable Implement cloud security best practices, including IAM, secrets management, encryption, and vulnerability management Troubleshoot complex production issues and drive continuous platform improvements Share technical expertise, mentor team members, and contribute to architecture and engineering best practices Requirements Strong hands-on experience in DevOps, Platform Engineering, or Site Reliability Engineering Proven experience designing, implementing, and operating solutions on Google Cloud Platform (GCP) Strong experience with Kubernetes (GKE preferred) and Docker in production environments Experience building and maintaining CI/CD pipelines using GitHub Actions, Argo CD, or similar CI/CD tools Hands-on experience with Infrastructure as Code tooling Solid understanding of cloud networking, including Virtual Networks, DNS, load balancing, IAM, VPNs, and security best practices Experience implementing monitoring, logging, and observability solutions (e.g., Prometheus, Grafana, Datadog, or similar tools) Proficiency in scripting and automation using Python, Go, or Bash Strong troubleshooting and problem-solving skills across cloud infrastructure and distributed systems Upper-Intermediate or higher English level for effective communication in a global environment Experience supporting AI-enabled platforms or machine learning infrastructure and/or familiarity with Vertex AI, Kubeflow, MLflow, Ray, or similar AI/ML platforms *would be appreciated) Familiarity with NVIDIA technologies, including GPU-enabled infrastructure, NVIDIA GPU Operator, CUDA, or NVIDIA AI Enterprise (nice to have) Experience providing technical leadership, mentoring engineers, and driving technical decisions (would be an advantage) Experience migrating enterprise workloads between clouds (is a plus) Experience in designing infrastructure architectures (would be desirable) SoftServe is an equal opportunity employer. Qualified applicants will receive consideration regardless of race, color, ancestry, ethnicity, national origin, religion, sex, sexual orientation, gender identity or expression, age, citizenship, disability, health condition, marital or family status, veteran status, or any other characteristic protected by applicable law.