Senior Platform Engineer

Job Responsibilities :

Razer is looking for a Senior Platform Engineer to join our Global IT Infrastructure team in Singapore. This role has two missions: building and running the cloud, Kubernetes and DevOps platforms behind Razer’s enterprise applications, and building the AI platform that takes internal AI agents from idea to secure, well-governed production. This is an engineering role, not a support role. The emphasis is on cloud, DevOps, AI platform engineering, automation, reliability and security across a hybrid Azure (primary), AWS and on-premises estate. You are a senior individual contributor with technical leadership responsibility: a self-directed engineer who combines engineering depth with methodical troubleshooting, and who is comfortable operating complex, international, multi-site environments. The role participates in an on-call rotation for major incidents and planned after-hours activities when required. Key Responsibilities

• Design, build and maintain scalable, secure and highly available cloud platforms, primarily on Azure, including networking, identity, compute, storage and hybrid connectivity, delivered through reusable Infrastructure as Code templates and platform components
• Design, build and operate container and Kubernetes platforms, primarily AKS, for enterprise applications, APIs and AI workloads, covering provisioning, scaling, upgrades, networking, security, observability and troubleshooting
• Automate provisioning, configuration, patching and lifecycle management with Infrastructure as Code (e.g. Terraform), and optimize cloud resources for performance, security and cost
• Build and maintain enterprise CI/CD and GitOps capabilities, including automated testing, security scanning, image management, deployment, rollback and release controls
• Lead modernization initiatives such as cloud migration, containerization and legacy retirement
• Design, deploy and operate the platform that hosts AI agents and LLM-based applications, using cloud AI services (e.g. Microsoft Foundry, Azure OpenAI, Amazon Bedrock, Amazon Bedrock AgentCore) and containers
• Integrate agents securely with enterprise systems through standard APIs, connectors and Model Context Protocol (MCP)
• Implement AI platform guardrails in line with Group Information Security and AI governance policies, including least-privilege agent identities, data access controls, audit logging, agent evaluation and versioning, runtime observability, and monitoring of AI usage and cost
• Mitigate AI-specific risks such as prompt injection and data leakage through platform design and controls
• Provide reusable templates, reference architectures and self-service environments, and help departments move AI and agentic use cases from prototype to production
• Implement centralized monitoring, logging, alerting and platform SLOs
• Act as technical lead during major incidents, and drive post-incident reviews through to permanent fixes
• Own backup, restore and disaster recovery, including scheduled DR tests against agreed RTO and RPO targets
• Embed security into platform design and pipelines (cloud IAM, secrets management, encryption), work with Group Information Security on vulnerabilities and compliance, and maintain platform standards, runbooks and change management practices
• Mentor engineers on platform engineering best practices
• Other duties as assigned

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