Responsibilities
1. Responsible for the exploration and development of AI functions in AI IDE, focusing on the server-side implementation of AI functions, covering but not limited to code generation, code understanding, knowledge Q&A, project understanding, PE, Al Agent, multi-modality, AI ecology, etc., presenting complex AI function interactions to users in an intuitive and easy-to-use way, and continuously optimizing user experience 2. Responsible for and improving AI The IDE's model application cost, end-to-end performance, project understanding, model effects and other specialties provide stable, efficient and high-experience services 3. Continue to follow the latest technology trends in the LLM field, provide innovative solutions based on the server-side needs of AI IDE, and promote the iteration and upgrade of server-side technology.
Qualifications
1. Bachelor degree or above, computer-related major, deep understanding of computer system principles, solid data structure and algorithm foundation, and programming capabilities 2. Proficient in at least one mainstream back-end development language (such as Rust, Golang, Java), and rich experience in back-end development and system design 3. Be familiar with common server-side basic technologies such as distributed systems, microservice architecture, database design and optimization, caching mechanisms and message queues 4. Have practical experience in API design, interface security, performance tuning and automated testing, and be able to independently design and implement high-quality back-end services 5. Be familiar with Prompt Engineering, understand Prompt optimization techniques, and have relevant project experience. Applicants with the following experience will be given priority: 1. Have a strong interest in AI technology and large language models, be willing to follow and explore the latest technology trends, and have good learning and problem-solving abilities 2. Have experience in AI application R&D related technologies, including but not limited to LangChain, Vector DBs, RAG, Embedding, etc. 3. Have experience in AI Agent construction 4. Have experience in Rust R&D 5. Be familiar with cloud native technologies (such as Docker, Kubernetes) and DevOps practices, and have relevant experience in operation and maintenance or automated deployment 6. Those with experience in contributing to open source projects or being active in the technical community will be given priority if they are passionate about AI technology, willing to follow up and explore the latest technologies and trends, and have good learning and problem-solving abilities.
