jobs in Wilmar International

全职 AI-Native Application Engineer 工作, 薪水, Wilmar International 公司招聘中 - Ricebowl

AI-Native Application Engineer

Wilmar International

Undisclosed

Singapore

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工作地点

  • Singapore

职位描述

岗位职责

About the Role

Wilmar International runs a broad landscape of business applications — internal tools, web and mobile applications, APIs, and system integrations — built primarily in Java, .NET Core, and TypeScript. As an AI-Native Application Engineer, you will design, build, and maintain these applications, using AI-assisted coding tools (e.g., GitHub Copilot, Claude Code, Cursor) as a core part of your everyday workflow to design, code, test, debug, and document faster and to a higher standard. You will also develop AI-powered features and lightweight AI applications within our business systems — integrating LLM APIs, embedding AI assistants, and applying intelligent automation — bringing AI capabilities directly into the products you build.


Key Responsibilities

  • Design, build, and maintain business applications and services in Java, .NET Core, and TypeScript, spanning web, API, and integration layers.
  • Use AI-assisted coding tools as a core part of your daily workflow — code generation, refactoring, test generation, and documentation — to increase delivery speed without compromising code quality.
  • Apply effective prompt engineering and review discipline to get reliable, high-quality output from AI coding assistants, and critically review AI-generated code before it ships.
  • Build AI-powered features into business applications — such as integrating LLM APIs, embedding AI assistants, or adding intelligent automation — to enhance existing Java, .NET Core, and TypeScript applications.
  • Integrate applications with backend services, APIs, and databases, contributing to API and data model design within the existing enterprise architecture.
  • Follow the architecture, security, and coding standards set by Enterprise Architecture and Technical Development leadership, including standards for AI-assisted development.
  • Write automated tests and contribute to CI/CD pipelines to support fast, reliable releases.
  • Troubleshoot, debug, and optimise application performance in test and production environments.
  • Participate in enablement sessions and knowledge-sharing on AI-assisted development practices, and apply what’s shared in your own delivery work.
  • Document your work clearly — code comments, technical notes, and handover documentation — whether AI-assisted or hand-written.


Required Qualifications

  • Bachelor’s degree in Computer Science, Software Engineering, or a related field.
  • 3–6 years of software engineering experience building and shipping production applications in Java, .NET Core (C#), and/or TypeScript.
  • Daily, hands-on experience with AI-assisted coding tools (GitHub Copilot, Claude Code, Cursor, or similar), with strong instincts for prompting, reviewing, and correcting AI-generated code.
  • Solid software engineering fundamentals — OOP and design patterns, REST/GraphQL API design, relational and/or NoSQL databases, version control, and automated testing.
  • Practical experience with relevant frameworks (e.g., Spring Boot, ASP.NET Core, React, Angular, or Node.js) for your primary stack.
  • Familiarity with CI/CD pipelines and containerisation (e.g., Docker).
  • Ability to critically evaluate AI-generated code for correctness, security, and maintainability, rather than accepting suggestions uncritically.
  • Strong problem-solving skills and the ability to work independently on well-scoped features.
  • Working proficiency in English; Mandarin language skills are an advantage given regional stakeholder collaboration.


Preferred Qualifications

  • Experience building AI-powered application features using LLM APIs or GenAI services (e.g., Azure OpenAI, AWS Bedrock, Google Vertex AI).
  • Exposure to cloud platforms (Azure, AWS, or GCP).
  • Experience in agribusiness, manufacturing, supply chain, or FMCG is a plus.
  • Familiarity with Agile/Scrum delivery practices.
  • Genuine curiosity about new AI developer tools and enthusiasm for experimenting with them as they emerge.


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