Java/AI Engineer

Role : Java/AI Engineer Location: Sydney Type : Contract for 6 months Roles and Responsibilities: Have demonstrable experience leading and building scalable microservices and event-driven applications Can solve complex technical challenges from design through to production Address tech debt with a pragmatic, commercially focused approach Translate requirements into solid engineering deliverables Deliver reusable solutions used across teams and products Collaborate across teams and align technical decisions with business goals xpertise in observability and reliability practices, leveraging tools such as OpenTelemetry, Prometheus, Grafana and CloudWatch A solid understanding of security best practices, including Vault, AWS Secrets Manager and certificate management Experience with testing methodologies (TDD, BDD) and automation frameworks Ability to design and implement data-intensive applications and scalable architectures (API, microservices, event-driven, serverless) Knowledge of deployment strategies and SRE principles Interest or experience in AI/ML technologies and emerging tools Your Skills and Experience Programming: Java, TypeScript and JavaScript (Node.js) ,Springboot building scalable, high-performance services. Frameworks & Platforms: . Java, React (TypeScript), Springboot EE for RESTful APIs and enterprise applications. Architecture: Microservices, Domain-Driven Design (DDD), event-driven systems using RabbitMQ and/or Apache Kafka. Databases: SQL Server, PostgreSQL, and/or other relational/NoSQL databases – e.g., PostgreSQL and DynamoDB Cloud (AWS): EC2, Lambda, ECS/Fargate, RDS, DynamoDB, CloudFormation, CDK, CodePipeline, CodeBuild, CloudWatch. CI/CD: TeamCity, Octopus Deploy, GitHub & GitHub Actions. Containers: Kubernetes and Docker. Infrastructure as Code: Terraform, CloudFormation, Ansible. Quality Engineering: Strong advocate for automated testing and quality-driven delivery. You also bring (or are keen to grow) front-end engineering capability, with skills in TypeScript, React, and Next.js, highly regarded across our full-stack engineering practice and a key differentiator for delivering seamless end-to-end customer and developer experiences. AI & Chatbot Integration: Exposure to building AI-driven support tools, such as integrating with LLMs/ChatGPT for developer support. Knowledge of the Model Context Protocol (MCP) server concept or similar ChatGPT plugin development is a plus, as this squad owns an AI ChatBot for developer enablement