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Talentvis Singapore Pte Ltd. is seeking a Full Stack Engineer to develop scalable web applications and AI-powered solutions, covering frontend and backend, deployment, integration and optimisation.
You will build frontend with React.js and Next.js, create backend APIs with Node.js/Python, and integrate AI features such as LLMs, RAG and AI agents, deploying on cloud with CI/CD pipelines.
We are seeking a Full Stack Engineer to develop and maintain scalable web applications and AI-powered solutions. You will be responsible for end-to-end application development, from frontend and backend engineering to deployment, integration and ongoing optimisation.
Key Responsibilities
Design, develop and maintain responsive web applications and backend services.
Build frontend applications using React.js and/or Next.js.
Develop backend services and RESTful APIs using Node.js and/or Python.
Integrate AI capabilities into applications, including LLMs, RAG and AI agents.
Deploy and maintain applications using cloud and containerisation technologies.
Manage CI/CD pipelines, testing and application deployments.
Ensure application security, performance and reliability.
Troubleshoot issues and continuously improve application quality.
Requirements
Degree or Diploma in Computer Science, IT or a related discipline.
Experience in full-stack software development across frontend and backend.
Proficiency in JavaScript/TypeScript, React.js and/or Next.js.
Experience with Node.js and/or Python, including API development.
Exposure to LLM integration, RAG, AI agents or AI-powered application development.
Familiarity with AWS, Docker, Git and CI/CD practices.
Good understanding of application security, testing and software development best practices.
Added Advantages
Experience with LangChain, vector databases, Azure OpenAI or Microsoft Copilot.
Familiarity with Kubernetes and cloud infrastructure.
Experience in government or public-sector technology projects.
**We regret to inform that only shortlisted candidates would be notified**
EA License No: 04C3537
EA Personnel No: R22106683
EA Personnel Name: Yang Hui Shan, Sherri