Software Engr II

Job Overview

We are seeking a Full-Stack Engineer with development background and practical AI application implementation experience. You will be responsible for the end-to-end development and iteration of AI systems for small and medium-sized localized platforms including building services integrating local offline LLM capabilities implementing lightweight full-stack AI features and ensuring system stability performance and compliance.

Role Positioning: This is a .NET AI full-stack engineering role focused on application engineering and production delivery not model training or algorithm research. You will independently implement full-stack AI solutions covering backend AI service orchestration and frontend AI interactive development.

Key Responsibilities

• Design and develop stable Core services and standardized RESTful APIs to support business and AI scenarios for small and medium-sized localized platforms.
• Build enterprise AI applications based on local LLM services offline AI SDKs and local AI frameworks; implement end-to-end AI service orchestration including prompt management context scheduling streaming response processing logging and error handling.
• Build lightweight deployable local RAG solutions for small and medium scenarios covering document parsing embedding generation local vector retrieval context assembly and intelligent response generation.
• Implement full-stack AI features such as AI dialogue interfaces streaming interaction semantic search and document Q&A; optimize front-backend integration to guarantee system stability and user experience.
• Leverage AI tools to improve full-stack R&D efficiency including code generation refactoring automated testing and rapid prototyping.
• Conduct AI output quality validation system performance tuning and security optimization; maintain technical documentation and collaborate cross-functionally to drive product and technical iteration.
• Follow standard software engineering and Responsible AI principles to deliver stable lightweight and maintainable AI systems for small and medium-sized business platforms.

Basic Qualifications

• Bachelors degree or above in Computer Science Software Engineering or related technical fields.
• 3 years professional C#/.NET development experience proficient Core and WebAPI with practical experience building and maintaining small-to-medium scale business systems.
• Solid software engineering fundamentals with hands-on experience in asynchronous programming and performance tuning for local business systems.
• Familiar with network communication principles and socket programming.
• Solid frontend fundamentals with HTML/JavaScript/TypeScript; proficient in at least one mainstream framework (React/Angular/Vue/Blazor).
• Hands-on experience integrating LLM APIs/SDKs to build production AI applications.
• Deep understanding of core AI application technologies: RAG embedding vector search and prompt engineering.
• Capable of designing AI service orchestration exception handling monitoring and performance tuning.
• Proven experience building full-stack AI scenarios including streaming responses chat interaction and document Q&A.
• Familiar with AI content security data privacy compliance and Responsible AI practices.
• Strong independent troubleshooting and cross-team collaboration skills with fluent English for daily technical work.

Preferred Qualifications

• Familiar with lightweight open-source AI frameworks and local LLM integration solutions suitable for small and medium-sized platforms.
• Hands-on experience building lightweight RAG systems local knowledge bases and internal AI assistants for small and medium-sized platforms.
• Familiar with lightweight vector storage and local retrieval solutions suitable for small and medium-sized platforms including embedded vector libraries local file retrieval and lightweight standalone search engines.
• Hands-on experience with WebSocket/SSE streaming interaction and real-time AI full-stack development.
• Familiar with local deployment standalone service iteration local environment debugging and system observability.
• Experience in prompt optimization AI output evaluation and AI application performance tuning is a plus.
• Hands-on experience with C Rust or other system-level programming languages is a plus.

Core Tech Stack

Core Technologies: .NET Core C# WebAPI LLM API/SDK Integration Prompt Engineering Embedding Vector Search RAG AI Service Orchestration Streaming Interaction Full-Stack AI Development AI Quality Control & Security Compliance.