全职 Software Developer (Java - AI) (GC-SW) 工作, 薪水, ST Engineering 公司招聘中 - Ricebowl

Job Description:

• Contribute to all stages of the SDLC — from requirements analysis through to deployment and post-production support.
• Design, develop, and maintain scalable, high-availability Java-based applications, including support for legacy systems and progressive modernisation towards cloud-native microservices patterns.
• Build, deploy, and manage containerised applications using Docker, Kubernetes, and EKS on AWS/GCP.
• Apply DevSecOps practices across the development pipeline, including vulnerability assessment and remediation.
• Design and deploy AI-powered agents and workflows using Copilot Studio, Google Agent Builder, Dataiku, Outsystems, or equivalent platforms.
• Implement Generative AI solutions including RAG-based assistants, LLM-powered summarisation, and content generation using Azure OpenAI or equivalent.
• Integrate AI capabilities into enterprise systems via REST APIs, Graph API, and Power Automate workflows.
• Engage with business stakeholders to gather requirements, identify AI use case opportunities, define agent behaviours, and communicate solution designs.
• Conduct testing, debugging, and performance evaluation of Java applications, AI agents, and automation workflows.

Job Requirements:

The candidate should be able to develop and maintain Java-based enterprise applications, operate within cloud-native and DevSecOps environments on AWS/GCP, and actively design and deploy AI-powered solutions using platforms such as Microsoft 365 Copilot, Google Agent Builder, and GitHub Copilot. Strong communication skills to work with business stakeholders and translate requirements into technical solutions are essential.

Required Technical Skills:

• Proficiency in Java/J2EE, Spring Boot, Spring Framework, Hibernate/JPA, and RESTful web services.
• Working knowledge of Python and ReactJS for scripting, automation, and front-end integration tasks.
• Working knowledge of container orchestration using Kubernetes (K8S) and Amazon EKS — deployment, scaling, and management of containerised workloads.
• Experience building and maintaining CI/CD pipelines using GitLab CI, Jenkins, or GitHub Actions.
• Understanding of DevSecOps principles — SAST, DAST, dependency scanning, and secrets management integrated into the SDLC.
• Applied experience with SQL and NoSQL databases such as PostgreSQL, MSSQL, or MongoDB.
• In-depth knowledge of Git (branching strategies, pull requests, merge workflows) and build tools such as Maven, Gradle, and Docker.
• Hands-on experience with one or more AI/agent platforms: Microsoft 365 Copilot, Copilot Studio, Dataiku DSS, Google Agent Builder, OutSystems ODC, or equivalent — including plugins, connectors, and Graph API integrations.
• Understanding of AWS and/or GCP cloud platforms including compute, storage, networking, and managed services.
• Understanding of Generative AI concepts: LLMs, prompt engineering, Retrieval-Augmented Generation (RAG), and agentic AI patterns.
• Familiarity with Azure OpenAI Service or OpenAI APIs for embedding AI capabilities into applications.