Senior Full Stack Engineer, AI-Assisted Development

We are looking for a hands-on Senior Full Stack Engineer to design, build, secure and operate enterprise-grade digital products on Microsoft Azure. This is an AI-enabled engineering role where the successful candidate is expected to be familiar with modern AI-assisted development tools such as GitHub Copilot, Claude, ChatGPT or equivalent, and able to use them responsibly to improve coding productivity, technical problem-solving, test generation, documentation and delivery quality. This role sits within the Platform & Software Engineering Division and will contribute to JTC’s Digital Factory Platform by developing modern cloud-native applications, reusable engineering patterns and AI-enabled solutions that can move from concept to production with speed, quality and accountability. The successful candidate will work across the full application stack, covering responsive frontend development, Java and Python backend services, APIs, databases, cloud services, DevSecOps pipelines, observability and production support. They should be comfortable owning solutions from technical design through deployment and operations, while applying secure engineering practices, cloud-first thinking and AI-enabled development approaches. Key Responsibilities Build secure, scalable and maintainable backend services using Java, Spring Boot, Python, FastAPI or equivalent frameworks, with strong RESTful API and microservices design practices. Develop and integrate cloud-native solutions using Microsoft Azure services including App Service, Azure Functions, Azure Storage, Azure SQL Database, Azure API Management, Azure Service Bus, Event Grid, Key Vault, Azure Monitor, Application Insights and Microsoft Entra ID. Design and implement data access patterns using SQL and NoSQL databases, including schema design, query optimisation, ORM frameworks and secure data handling practices. Implement CI/CD pipelines using Azure DevOps, GitHub Enterprise and GitHub Actions to automate build, test, security scanning, deployment and release processes. Apply DevSecOps practices across the software delivery lifecycle, including secrets management, vulnerability management, secure coding, automated testing and compliance checks. Use Infrastructure as Code tools such as Bicep or Terraform to support repeatable environment provisioning and application deployment. Containerise and deploy applications using Docker and Kubernetes, including Azure Kubernetes Service where appropriate. #J-18808-Ljbffr