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Software Engr II
Honeywell —广州市
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Participate in the software requirement analysis and feature design. Basic knowledge of agile software engineering methodologies would be a plus.

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Software Engr II

Honeywell -
广州市

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Job Overview

We are seeking a Full-Stack Engineer with solid .NET 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 stable .NET 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.

Basic Qualifications

Bachelor’s degree or above in Computer Science, Software Engineering or related technical fields.
3+ years professional C#/.NET development experience, proficient in .NET 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.

Key Responsibilities

Design and develop stable, lightweight .NET 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.

Honeywell helps organizations solve the world's most complex challenges in automation, the future of aviation and energy transition. As a trusted partner, we provide actionable solutions and innovation through our Aerospace Technologies, Building Automation, Energy and Sustainability Solutions, and Industrial Automation business segments – powered by our Honeywell Forge software – that help make the world smarter, safer and more sustainable.

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