Job Description

• We are looking for a hands-on Platform Engineer with strong Microsoft Azure expertise and practical AI literacy to help build, scale and operate Digital Factory Platform.
• The Digital Factory Platform provides a secure, governed and automation-led foundation that enables product teams to move digital products and AI experiments from sandbox to production faster, safely and with clear operational accountability.
• Sitting within the Platform & Software Engineering Division, you will develop reusable platform capabilities covering cloud infrastructure, Infrastructure-as-Code (IaC), CI/CD, developer self-service, identity and access management, observability, DevSecOps, FinOps and AI application enablement.
• You will play a key role in simplifying cloud complexity by creating secure, repeatable golden paths that development and product teams can consume with minimal friction.

Responsibilities

Platform Engineering & Cloud Infrastructure

• Design, build and operate Azure-based platform capabilities across sandbox, QA, UAT and production environments.
• Develop and maintain reusable Infrastructure-as-Code (IaC) templates using Azure Bicep, Terraform or equivalent technologies.
• Build self-service platform capabilities and golden paths covering environment provisioning, application templates, deployment patterns, access requests and approved engineering tools.
• Establish scalable and secure cloud-native architecture patterns for applications and shared platform services.

CI/CD & DevSecOps

• Design and maintain CI/CD and GitOps pipelines using Azure DevOps, GitHub, ShipHATS or equivalent platforms.
• Automate build, testing, security scanning, deployment, environment promotion, rollback and release quality gates.
• Embed security, reliability and compliance requirements directly into engineering workflows through automated controls, policy-as-code and platform guardrails.
• Implement secure software delivery practices covering secrets management, vulnerability scanning and compliance validation.

AI & Application Enablement

• Support the transition of AI-generated, experimental and prototype applications into secure and evaluable MVPs.
• Apply production-readiness standards covering secure architecture, containerisation, API management, monitoring, deployment and operational support.
• Support the integration, security and operation of AI/ML services on Azure.
• Use AI-assisted development tools such as GitHub Copilot, Microsoft Copilot, Claude or equivalent tools to improve engineering productivity, testing, documentation and code quality.

Identity, Security & Governance

• Implement identity and access management using Microsoft Entra ID, RBAC, Privileged Identity Management (PIM), Conditional Access and least-privilege principles.
• Support enterprise identity integration involving Active Directory, group-based access, authentication flows and hybrid identity.
• Apply modern authentication and authorisation standards including OAuth 2.0, OpenID Connect, SAML and JWT.
• Ensure platform capabilities comply with enterprise and government security, governance and operational requirements.

Observability, Reliability & FinOps

• Implement monitoring and observability using Azure Monitor, Log Analytics and service health dashboards.
• Establish platform metrics covering system health, deployment performance, incidents, compliance and cost.
• Support FinOps practices through resource tagging, budget alerts, cost allocation, token-cost tracking and showback reporting.
• Contribute to production reliability, incident management and continuous platform improvement.

Collaboration & Platform Adoption

• Work closely with product owners, developers, security, audit, finance and leadership stakeholders.
• Translate platform architecture into reusable engineering patterns, templates, APIs and self-service capabilities.
• Develop clear technical documentation, operating procedures and platform standards.
• Gather adoption feedback and continuously improve platform capabilities and developer experience.

Required Skills & Experience

• 10+ years of hands-on engineering experience, with significant experience designing, building and operating Microsoft Azure infrastructure in enterprise or regulated environments.
• Strong hands-on experience with Azure services such as:
• Azure Landing Zones
• Azure Policy
• Azure Container Apps / App Service
• Azure API Management
• Azure Monitor and Log Analytics
• Microsoft Defender for Cloud
• Azure Cost Management
• Hands-on experience working within Government Commercial Cloud (GCC) environments, including government security, compliance, identity, networking and operational controls.
• Extensive experience with Infrastructure-as-Code, preferably Azure Bicep and/or Terraform.
• Strong experience designing and operating CI/CD and GitOps pipelines using Azure DevOps, GitHub, ShipHATS or equivalent platforms.
• Strong knowledge of DevSecOps, including automated security controls, vulnerability scanning, secrets management, policy-as-code and release quality gates.
• Strong experience with Microsoft Entra ID, RBAC, Conditional Access, PIM, access reviews and least-privilege access governance.
• Practical experience using AI-assisted engineering tools such as GitHub Copilot, Microsoft Copilot, Claude or equivalent.
• Experience integrating, securing or operating AI/ML services on Azure and preparing AI-enabled applications for production.
• Working knowledge of Active Directory and enterprise/hybrid identity integration.
• Understanding of SAML, OpenID Connect, OAuth 2.0 and JWT.
• Working knowledge of containers, APIs, cloud-native architectures and production-readiness practices.
• Experience supporting at least one production cloud-native application or shared platform capability, including deployment, monitoring, reliability or operational support.
• Ability to translate architecture into reusable platform patterns, templates and developer self-service capabilities.
• Strong communication and documentation skills, with the ability to engage both technical and non-technical stakeholders.
• Comfortable working in an Agile, product-oriented engineering environment.

Preferred Skills

• Experience with Azure OpenAI, Microsoft Fabric, Synapse, AI application platforms, data products or AI governance.
• Experience developing internal developer platforms, developer portals, platform APIs, self-service workflows or golden-path templates.
• Experience within Singapore public-sector, government cloud or other highly regulated environments.
• Knowledge of SRE practices, observability, incident response automation, Microsoft Sentinel, alert routing and service health monitoring.
• Understanding of FinOps, cloud cost optimisation, TCO modelling and cost accountability.
• Familiarity with engineering and collaboration tools such as Jira, Confluence, GitHub, Azure DevOps, ShipHATS and Copilot.