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Tap Growth ai Linkedin ยท Posted 2d ago

Senior Cloud Platform Engineer

Singapore

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๐ŸŒŸ We're Hiring: Senior Cloud Platform Engineer! ๐ŸŒŸ

We are seeking an experienced and innovative Senior Cloud Platform Engineer to lead our cloud infrastructure initiatives. The ideal candidate will possess extensive knowledge of cloud technologies, architecture, and best practices to ensure optimal performance and security of our systems.

๐Ÿ“ Location: Singapore, Singapore
โฐ Work Mode: Work from Office
๐Ÿ’ผ Role: Senior Cloud Platform Engineer

Key Responsibilities
1. Design, build and operate Azure-based platform capabilities that support the Digital Factory across sandbox,
QA, UAT and production environments.
2. Develop and maintain infrastructure-as-code templates using tools such as Azure Bicep, Terraform or
equivalent, enabling consistent and repeatable environment provisioning.
3. Build self-service golden paths for product teams, including environment provisioning, application templates,
deployment patterns, access requests and approved tooling.
4. Implement CI/CD pipelines using Azure DevOps, GitHub, ShipHATS or equivalent platforms to automate
build, test, release, promotion and rollback processes.
5. Embed security, reliability and compliance controls into platform workflows through policy-as-code, automated
checks and guardrails.
6. Support the hardening of AI-generated or experimental applications into evaluable MVPs by applying secure-
by-default architecture, containerization, API management, monitoring and deployment baselines.
7. Implement identity and access controls using Microsoft Entra ID, role-based access control, Privileged Identity
Management, Conditional Access and least-privilege practices.
8. Develop observability capabilities using Azure Monitor, Log Analytics, dashboards and business-relevant
platform metrics covering cost, health, delivery, incidents and compliance.
9. Support FinOps and TCO transparency through resource tagging, budget alerts, cost allocation, token-cost
tracking and show back reporting to product owners.
10. Collaborate with product owners, developers, security, audit, finance and leadership stakeholders to ensure
platform capabilities are practical, governed and aligned to business outcomes.
11. Document reusable patterns, operating procedures and platform decisions to improve adoption,
maintainability and knowledge retention within JTC.
Required Skills and Experience
1. 10+ years of hands-on engineering experience, including significant experience designing, building, managing
and operating cloud infrastructure on Microsoft Azure in enterprise or regulated environments.
2. Deep hands-on experience with Azure platform services such as Azure Landing Zones, Azure Policy, Azure
Container Apps, Azure App Service, API Management, Azure Monitor, Log Analytics, Defender for Cloud and
Azure Cost Management.
3. Hands-on experience operating in Government Commercial Cloud (GCC) environments, including working
within government cloud governance, security, compliance, identity, network and operational controls.
4. Extensive hands-on experience with infrastructure-as-code, automated provisioning and configuration
management using Azure Bicep, Terraform or equivalent tools.
5. Extensive experience designing and operating CI/CD and GitOps pipelines using Azure DevOps, GitHub,
ShipHATS or similar platforms, including automated build, test, security scanning, deployment promotion,
rollback and release quality gates.

6. Strong hands-on experience applying DevSecOps practices and implementing platform guardrails, including
secure software delivery, automated quality checks, secrets management, vulnerability scanning, policy-as-
code and compliance controls.
7. Strong hands-on experience in identity and access engineering using Microsoft Entra ID, RBAC, Conditional
Access, PIM, access reviews and least-privilege access governance.
8. Practical AI literacy and experience using AI-assisted development tools such as Claude, GitHub Copilot,
Microsoft Copilot or equivalent tools to improve software delivery, code quality, documentation, testing or
developer productivity.
9. Experience integrating, securing and operating AI/ML platform services on Azure, including access controls,
network security, service configuration, monitoring and production-readiness controls for AI-enabled
applications.
10. Working knowledge of Active Directory and enterprise identity integration concepts, including directory
services, group-based access, authentication flows and hybrid identity considerations.
11. Working knowledge of modern authentication and authorization standards, including SAML, OpenID Connect,
OAuth 2.0, JWT and related enterprise application integration patterns.
12. Working knowledge of containerization, APIs, cloud-native application patterns and production-readiness
practices.
13. Experience supporting at least one production cloud-native application or shared platform capability, with
responsibility for reliability, monitoring, deployment or operational support.
14. Ability to translate platform architecture into reusable engineering patterns, templates, developer self-service
capabilities and platform services that product teams can consume with minimal friction.
15. Strong documentation and communication skills, with the ability to explain technical concepts to both
engineering and non-technical stakeholders.
16. Comfortable working in an agile, product-oriented environment where platform capabilities are built
incrementally and improved through adoption feedback.
Preferred Skills
1. Experience with AI application platforms, Azure OpenAI, Microsoft Fabric, Synapse, data products or AI
governance patterns.
2. Experience building developer portals, internal platforms, platform APIs, self-service workflows or golden-path
engineering templates.
3. Familiarity with public sector cloud environments, government security requirements or regulated enterprise
environments.
4. Experience with observability, SRE practices, incident response automation, Microsoft Sentinel, alert routing
and service health dashboards.
5. Understanding of FinOps practices, cloud cost optimization, TCO modelling and cost accountability
mechanisms.
6. Exposure to tools such as Jira, Confluence, GitHub, Azure DevOps, ShipHATS, Copilot or other modern
engineering productivity tools.


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