GCP Administrator

Accountabilities:: Administer and maintain GCP projects, including IAM roles, permissions, service accounts, and organizational policies. Provision, configure, and manage core GCP services including Compute Engine, GKE, Cloud Storage, Cloud SQL, BigQuery, VPC, Cloud Functions, and Pub/Sub. Deploy, configure, and administer enterprise AI agent platforms such as Google Agentspace, Vertex AI Agent Builder, or comparable solutions, including agent provisioning, access controls, data connectors, and lifecycle management. Manage integrations between AI agents, internal data sources, APIs, and third-party systems. Monitor infrastructure performance, availability, and health using Cloud Monitoring, Cloud Logging, and related observability tools. Design and maintain cloud networking components including VPCs, subnets, firewall rules, load balancers, VPNs, and associated connectivity. Implement least-privilege access controls and security policies, including governance of AI agents and automated workflows. Establish and maintain backup, disaster recovery, and business continuity processes to support resilient operations. Monitor cloud usage and spending, implement cost-control measures and budget alerts, and track consumption associated with AI and agent workloads. Automate infrastructure provisioning and configuration using Terraform, Deployment Manager, or comparable Infrastructure-as-Code tools. Collaborate with DevOps and development teams to support CI/CD pipelines, application deployments, and cloud infrastructure requirements. Ensure infrastructure and AI agent environments comply with organizational security standards, data governance policies, and applicable regulatory requirements. Troubleshoot and resolve infrastructure incidents, service disruptions, and issues affecting cloud or AI agent platforms. Maintain accurate documentation covering cloud architecture, agent configurations, access controls, and operational procedures. Stay current with GCP product updates, emerging cloud technologies, generative AI and agent capabilities, and industry best practices. Requirements: Bachelor's degree in Computer Science, Information Technology, or a related discipline, or equivalent practical experience. 3+ years of hands-on experience administering Google Cloud Platform environments. Strong knowledge of core GCP services, particularly Compute Engine, GKE, Cloud Storage, IAM, VPC, and Cloud SQL. Hands-on experience or familiarity with enterprise AI agent platforms such as Google Agentspace, Vertex AI Agent Builder, or similar technologies used to deploy and manage AI agents at an organizational level. Practical experience with Infrastructure-as-Code, with Terraform preferred. Proficiency in scripting and automation using Python, Bash, or a comparable language. Strong understanding of networking fundamentals, including DNS, VPNs, load balancing, firewalls, and cloud connectivity. Experience with monitoring and logging tools such as Cloud Monitoring, Cloud Logging, or comparable third-party platforms. Knowledge of cloud security best practices, compliance frameworks, data governance, identity management, and access controls, including considerations for AI workloads. Familiarity with CI/CD pipelines and modern DevOps practices. Strong troubleshooting, analytical, documentation, and problem-solving skills. Ability to work independently in a fully remote environment while collaborating effectively with development, DevOps, security, and other technical stakeholders. Google Cloud certification, such as Associate Cloud Engineer, Professional Cloud Architect, or Professional Cloud DevOps Engineer, is preferred. Strong interest in emerging cloud, generative AI, and enterprise automation technologies is an advantage. Benefits: Full-time, long-term contract position. 100% remote work, with candidates able to work from anywhere in India. Consistent Monday-to-Friday schedule of 8 hours per day, totaling 40 hours per week. Opportunity to work extensively with Google Cloud Platform and modern cloud infrastructure technologies. Hands-on exposure to enterprise AI agents, generative AI platforms, and AI-driven automation workflows. Opportunity to strengthen expertise across Infrastructure-as-Code, DevOps, cloud security, networking, monitoring, and disaster recovery. Long-term opportunity to contribute to scalable, secure, and resilient cloud infrastructure. Fully distributed working environment offering flexibility and autonomy. Collaboration with development and DevOps teams on modern cloud-native applications and deployments.