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Overview
We are looking for a hands-on Senior Full Stack Engineer to design, build, secure, deploy, and operate enterprise-grade digital products on Microsoft Azure.
This is an AI-enabled engineering role where you will leverage modern AI-assisted development tools such as GitHub Copilot, Claude, ChatGPT, or equivalent to enhance coding productivity, technical problem-solving, test generation, documentation, and overall delivery quality.
As part of the Platform & Software Engineering Division, you will contribute to JTC's Digital Factory Platform, developing cloud-native applications, reusable engineering patterns, and AI-enabled solutions that can move efficiently from concept to production.
You will work across the full application stack, including React/TypeScript frontend development, Java and Python backend services, APIs, databases, Azure cloud services, DevSecOps, CI/CD, observability, and production support.
Key Responsibilities
Design, develop, and maintain scalable, secure, and enterprise-grade full stack applications using React, TypeScript, and JavaScript.
Develop backend services and APIs using Java, Spring Boot, Python, FastAPI, or equivalent frameworks.
Design and implement RESTful APIs, microservices, and system integrations following modern engineering practices.
Develop cloud-native solutions using Microsoft Azure services such as:
Azure App Service and Azure Functions
Azure API Management
Azure SQL Database and Azure Storage
Azure Service Bus and Event Grid
Azure Key Vault
Azure Monitor and Application Insights
Microsoft Entra ID
Design and implement data solutions using SQL and NoSQL databases, including schema design, query optimisation, ORM frameworks, and secure data handling.
Build and maintain CI/CD pipelines using Azure DevOps, GitHub Enterprise, and/or GitHub Actions.
Apply DevSecOps and secure software development practices, including secrets management, vulnerability scanning, automated testing, secure coding, and compliance checks.
Implement Infrastructure as Code (IaC) using Bicep, Terraform, or equivalent tools.
Containerise and deploy applications using Docker and Kubernetes/AKS where appropriate.
Integrate AI capabilities into applications using Azure AI Foundry, Azure OpenAI, Copilot services, or equivalent platforms where relevant.
Use AI-assisted development tools such as GitHub Copilot, Claude, and ChatGPT for coding, refactoring, test generation, documentation, and technical problem-solving while maintaining appropriate human review and security controls.
Participate in technical design, architecture reviews, and integration planning to ensure solutions are secure, scalable, reliable, and maintainable.
Support production environments through troubleshooting, performance optimisation, monitoring, alerting, observability, and incident resolution.
Collaborate with product owners, business users, platform engineers, security teams, and other stakeholders within Agile delivery teams.
Maintain technical documentation, engineering decisions, reusable patterns, and operational procedures.
Required Skills & Experience
Bachelor's degree in Computer Science, Software Engineering, Information Systems, or a related discipline.
Minimum 10 years of hands-on software development experience, including ownership of enterprise application design, delivery, deployment, and production support.
Strong full stack development experience with modern frontend and backend technologies.
Strong hands-on experience with React and TypeScript; exposure to Angular or Vue.js is advantageous.
Strong backend development experience using Java and/or Python, with frameworks such as:
Spring Boot
FastAPI
Flask
Django
Or equivalent frameworks
Strong experience developing REST APIs, microservices, and system integrations.
Minimum 3 years of hands-on Microsoft Azure experience within a production environment.
Experience with Azure PaaS and cloud-native services, particularly App Service, Azure Functions, API Management, Azure SQL Database, Azure Storage, and Key Vault.
Experience implementing authentication and authorisation using Microsoft Entra ID, Managed Identity, and RBAC.
Practical experience with AI-assisted development tools such as GitHub Copilot, Claude, ChatGPT, or equivalent.
Working knowledge of Infrastructure as Code, using Bicep, Terraform, or equivalent.
Experience with Docker, containerised applications, Kubernetes, and/or Azure Kubernetes Service (AKS).
Good understanding of secure application development, including secrets management, security scanning, vulnerability management, and secure configuration.
Strong troubleshooting, debugging, performance optimisation, and production support capabilities.
Experience working within Agile product delivery teams and collaborating across engineering, business, product, security, and operations functions.
Ability to translate business and product requirements into practical technical designs, architecture options, and implementation plans.
Preferred Skills
Experience working within Singapore Government Commercial Cloud (GCC) or other regulated enterprise environments.
Experience integrating AI capabilities using Azure AI Foundry, Azure OpenAI, or Copilot services.
Experience with platform engineering, internal developer platforms, developer portals, or reusable engineering templates.
Experience implementing cloud security controls including RBAC, Managed Identity, secrets management, network controls, and secure service-to-service communication.
Experience with event-driven architectures using Azure Service Bus, Event Grid, or equivalent messaging technologies.
Familiarity with domain-driven design, microservices architecture, and enterprise integration patterns.
Experience with observability and monitoring using Azure Monitor, Application Insights, logs, dashboards, traces, and application health metrics.
Familiarity with engineering and collaboration tools such as Jira, Confluence, GitHub, and Azure DevOps.
Key Competencies
Strong software engineering fundamentals with a focus on clean, scalable, and maintainable code.
Ability to work confidently across the full technology stack, including frontend, backend, APIs, databases, cloud infrastructure, and production environments.
Strong cloud-first and cloud-native mindset, particularly within the Microsoft Azure ecosystem.
Strong ownership and accountability from solution design through development, deployment, monitoring, and production support.
Ability to communicate technical concepts and trade-offs clearly to business, product, security, and engineering stakeholders.
Strong analytical, troubleshooting, and problem-solving capabilities.
Ability to balance delivery speed, security, scalability, reliability, and long-term maintainability.
Willingness to continuously learn and adopt modern engineering and AI-enabled development practices.
Ability to use AI tools responsibly to improve productivity and quality without compromising security, maintainability, or engineering accountability.