GCP DevOps with AI

Title: DevOps GCP with AI Company: KR3 Information Systems Role: Remote Shift Timings: 2:00 PM - 11:00 PM IST Role Overview We are looking for a motivated and technically strong GCP DevOps Engineer with 2+ years of experience in cloud infrastructure, CI/CD automation, and containerized deployments on Google Cloud Platform (GCP). The ideal candidate should also have basic exposure or working knowledge of AI/ML environments, such as supporting ML pipelines, model deployments, or understanding MLOps concepts. This role is ideal for someone who has hands-on DevOps experience and is interested in working on AI-enabled cloud platforms.

Required Skills 2+ years of experience in DevOps / Cloud Engineering. Hands-on experience with Google Cloud Platform (GCP). Strong understanding of Kubernetes and Docker. Experience with CI/CD tools. Knowledge of Terraform or Infrastructure as Code (IaC). Basic scripting knowledge (Python, Bash, or similar). Understanding of Linux environments.

Preferred / Good to Have (AI Exposure) Basic understanding of AI/ML concepts. Exposure to Vertex AI, AI Platform, or ML model deployment. Knowledge of MLOps practices. Experience supporting ML pipelines or data engineering workflows. Familiarity with GenAI concepts is a plus. What We’re Looking For Strong problem-solving mindset. Eagerness to learn AI-integrated cloud environments. Ability to work in a collaborative and fast-paced team.

Key Responsibilities Deploy, manage, and optimize applications on Google Cloud Platform (GCP). Work with GKE (Google Kubernetes Engine), Compute Engine, Cloud Storage, and related services. Build and maintain CI/CD pipelines using tools like Jenkins, GitHub Actions, or GitLab CI. Implement Infrastructure as Code (IaC) using Terraform or similar tools. Manage containerized environments using Docker and Kubernetes. Monitor system performance using GCP monitoring/logging tools. Support deployment and infrastructure needs for AI/ML workloads or ML pipelines. Collaborate with development and data teams to streamline deployments. Ensure cloud security best practices and cost optimization.

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