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Jobs(31,361)/AI Engineer Role(741)/patsnap (22) - AI Fullstack Engineer
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patsnap

patsnap - AI Fullstack Engineer

Singapore2d ago
In OfficeMidAPACArtificial IntelligenceSemiconductorsAI EngineerGitReactTypeScriptPythonFastAPIDocumentationReportingD3.jsJavaData VisualizationNode.jsSpring BootPostgreSQLMySQLWebSocketFull StackB2BVector

Requirements

• Bachelor's degree in Computer Science, Software Engineering, or related fields, with 3+ years of full-stack development experience and strong frontend engineering capability. • Proficient in React or Vue, TypeScript, state management, responsive design, and modern frontend development practices. • Experience building complex data visualizations using libraries such as ECharts, AntV, D3.js, or similar frameworks. • Proficient in Python and experienced with backend development using FastAPI (or similar frameworks) for building RESTful APIs and AI application services. • Experience with Node.js and/or Java (Spring Boot) for backend service development is a plus, with the ability to design, develop, and debug RESTful APIs. • Experience with relational databases (e.g., MySQL or PostgreSQL), API integration, and backend service architecture. • Familiar with real-time communication technologies such as Server-Sent Events (SSE), WebSocket, or streaming APIs, especially for AI chat, agent workflows, and long-running inference tasks.or streaming APIs, especially for AI chat and long-running task scenarios. • Proficient with Git, frontend build tools, deployment workflows, and CI/CD practices. • Strong problem-solving skills and the ability to translate business requirements into scalable technical solutions. • Good communication skills for cross-regional collaboration and the ability to read English technical documentation and fluent in English. • Experience building B2B SaaS products, scientific research platforms, or systems related to semiconductors, materials, manufacturing, or industrial domains. • Hands-on experience developing AI applications, AI Agents, workflow builders, prompt management systems, or AI Skill/Tool integration platforms. • Familiarity with LLM ecosystems, including model APIs, Retrieval-Augmented Generation (RAG), vector databases, semantic search, and AI application architectures. • Exposure to AI algorithm development, model evaluation, prompt engineering, or data processing pipelines is a plus, but not required. • Understanding of streaming AI interactions, multi-step agent workflows, and user experience design for AI products. • Experience working in global and distributed engineering teams.

Responsibilities

• Develop frontend architecture for AI Agent based on mainstream frameworks, build modules including AI chat, knowledge base search, data visualization, workflow orchestration and auto AI report preview. • Integrate LLM, retrieval and customized AI Skill APIs, implement streaming response, long-content rendering and professional interaction logic for AI scenarios. • Build lightweight backend services with Node.js, develop APIs and conduct database access to complete full-link joint debugging independently. • Develop visualization dashboards for semiconductor parameters, process curves and benchmark data; support filtering, batch export and drag operations. • Standardize frontend components, optimize loading performance, large-data rendering and code maintainability. • Cooperate with global cross-functional teams to iterate features, fix online issues and match industrial workflow requirements. • Manage frontend deployment, CI/CD and monitoring to guarantee stable online operation.

Benefits

• Work on high-growth vertical AI track combining semiconductor and large model technology, build differentiated technical competitiveness. • Role prioritizes frontend strengths with only basic backend needed; grow into an AI application frontend specialist or full-stack expert. • Central position in product development with high autonomy in interaction and component design. • Competitive compensation aligned with international tech standards, global teamwork opportunities and clear long-term career development paths. • All AI interaction and visualization assets can be accumulated as portfolio for future career advancement.

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