Platform Engineer - Microsoft Azure (Public Sector)
Summary
Build and scale a secure, governed Azure platform for JTC’s Digital Factory, enabling AI experiments and digital products to move from sandbox to production with automated CI/CD, IaC, FinOps, and developer self-service.
About the Role
We are looking for a hands-on Platform Engineer with practical AI literacy to help build and scale JTC's Digital Factory Platform on Microsoft Azure. The platform is designed as a self-service, governed and automation-led foundation that enables product teams to move AI experiments and digital products from sandbox to production faster, safer and with clearer accountability.
This role sits within the Platform & Software Engineering Division and will support the development of reusable platform capabilities across infrastructure provisioning, CI/CD delivery, AI-assisted development, AI application hardening, identity and access, observability, FinOps, compliance automation and developer self-service. The successful candidate will help turn cloud complexity into secure, repeatable golden paths that product teams can consume with minimal friction.
Key Responsibilities
- Design, build and operate Azure-based platform capabilities that support the Digital Factory across sandbox, QA, UAT and production environments.
- Develop and maintain infrastructure-as-code templates using tools such as Azure Bicep, Terraform or equivalent, enabling consistent and repeatable environment provisioning.
- Build self-service golden paths for product teams, including environment provisioning, application templates, deployment patterns, access requests and approved tooling.
- Implement CI/CD pipelines using Azure DevOps, GitHub, ShipHATS or equivalent platforms to automate build, test, release, promotion and rollback processes.
- Embed security, reliability and compliance controls into platform workflows through policy-as-code, automated checks and guardrails.
- 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.
- Implement identity and access controls using Microsoft Entra ID, role-based access control, Privileged Identity Management, Conditional Access and least-privilege practices.
- Develop observability capabilities using Azure Monitor, Log Analytics, dashboards and business-relevant platform metrics covering cost, health, delivery, incidents and compliance.
- Support FinOps and TCO transparency through resource tagging, budget alerts, cost allocation, token-cost tracking and show back reporting to product owners.
- Collaborate with product owners, developers, security, audit, finance and leadership stakeholders to ensure platform capabilities are practical, governed and aligned to business outcomes.
- Document reusable patterns, operating procedures and platform decisions to improve adoption, maintainability and knowledge retention within JTC.
Required Skills and Experience
- 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.
- 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.
- Hands-on experience operating in Government Commercial Cloud (GCC) environments, including working within government cloud governance, security, compliance, identity, network and operational controls.
- Extensive hands-on experience with infrastructure-as-code, automated provisioning and configuration management using Azure Bicep, Terraform or equivalent tools.
- 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.
- 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.
- Strong hands-on experience in identity and access engineering using Microsoft Entra ID, RBAC, Conditional Access, PIM, access reviews and least-privilege access governance.
- 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.
- 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.
- Working knowledge of Active Directory and enterprise identity integration concepts, including directory services, group-based access, authentication flows and hybrid identity considerations.
- Working knowledge of modern authentication and authorization standards, including SAML, OpenID Connect, OAuth 2.0, JWT and related enterprise application integration patterns.
- Working knowledge of containerization, APIs, cloud-native application patterns and production-readiness practices.
- Experience supporting at least one production cloud-native application or shared platform capability, with responsibility for reliability, monitoring, deployment or operational support.
- 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.
- Strong documentation and communication skills, with the ability to explain technical concepts to both engineering and non-technical stakeholders.
- Comfortable working in an agile, product-oriented environment where platform capabilities are built incrementally and improved through adoption feedback.
Preferred Skills
- Experience with AI application platforms, Azure OpenAI, Microsoft Fabric, Synapse, data products or AI governance patterns.
- Experience building developer portals, internal platforms, platform APIs, self-service workflows or golden-path engineering templates.
- Familiarity with public sector cloud environments, government security requirements or regulated enterprise environments.
- Experience with observability, SRE practices, incident response automation, Microsoft Sentinel, alert routing and service health dashboards.
- Understanding of FinOps practices, cloud cost optimization, TCO modelling and cost accountability mechanisms.
- Exposure to tools such as Jira, Confluence, GitHub, Azure DevOps, ShipHATS, Copilot or other modern engineering productivity tools.
What Success Looks Like
- Product teams can provision governed Azure environments in minutes instead of weeks.
- Developers have clear, reusable golden paths for building, testing, deploying and operating applications.
- AI experiments can be hardened into secure, observable and evaluable MVPs with minimal manual rework.
- Cost, token usage, ownership, incidents and compliance posture are visible to the right stakeholders through dashboards and automated reporting.
- Security and compliance controls are embedded into the platform by default rather than handled as manual afterthoughts.
- The platform continuously improves based on product team feedback, adoption metrics and business outcomes.
Ideal Candidate Profile
The ideal candidate is a practical platform builder who enjoys turning architecture into working capabilities. They should be comfortable engineering reusable Azure services, automating repeatable work, applying security and compliance guardrails, and improving the developer experience for product teams. They should also be outcome-oriented, able to balance speed with governance, and motivated by building a platform that helps JTC deliver digital products and AI solutions more efficiently.