Editorial summary

The company seeks an Infrastructure Lead specialized in Google Cloud Platform to design, deploy, automate, and secure cloud architectures on GCP. The role involves collaborating with internal stakeholders and delivery teams, setting priorities, and ensuring end-to-end service delivery while acting as the primary escalation point for client issues. Key requirements include strong experience in cloud architecture, GCP, automation, security, and stakeholder management, with a track record of leading operations and maintenance aligned to contractual obligations. The position offers a salary of 13,500.

This summary is AI-generated and may contain inaccuracies. Please refer to the full job description below.

Job description

[This job https://singapore.job-q.com/jobs/detail/infrastructure-lead-google-cloud-platform-37244 first appeared in Job-Q.com on 10 Oct 2026]

Responsibilities:

• Leading and implementing cloud architecture solutions with a focus on design, deployment, automation, and security on the Google Cloud Platform (GCP)
• Collaborate with internal application stakeholders, senior management, project leadership, and delivery teams
• Set priorities and ensure alignment of operations and maintenance with contractual obligations.
• Maintain accountability for end-to-end service delivery.
• Act as the focal point for client escalations related to issues and incidents
• Ensure KPI reports on service delivery progress are delivered
• Identify, develop, implement, and document process improvements to enhance customer service delivery
• Proactively identify opportunities for service expansion and improvement
• Work with Account Managers to develop identified opportunities
• Cultivate industry partnerships
• Manage developer communities
• Provide strong leadership to project and application teams

Requirements:

• Hands-on GCP experience in large enterprise-scale projects within SI environment
• Hands on experience with Python and Shell Scripting
• Experience across the software development and maintenance lifecycle
• Exposure to AWS or Microsoft Azure
• Exposure to AI Technologies, Agentic Workflows, AI Solutioning, LLM Optimization

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