Ai 应用研发工程师
Tasks
- Analyze requirements for large language model applications
- Build agent workflows
- Conduct technical reviews and code review
- Develop and deliver AI applications
- Develop reusable components SDKs and engineering standards
- Implement intelligent dialogue systems
- Implement prompt management evaluation and monitoring alerts
- Improve prompt engineering and optimization
- Optimize performance concurrency and cost
- Optimize retrieval augmented generation
- Plan and build AI engineering platform and tools
- Reduce hallucinations and improve response stability
- Select technical architecture and design solutions
- Set up deployment pipeline and low cost inference services
- Track industry trends and apply relevant techniques
- Tune vector database and embedding pipelines
Perks/Benefits
- N/A
Skills/Tech-stack
Agent | Cost governance | Docker | Embeddings | Evaluation | Inference Optimization | Java | MLOps | Message Queue | Model Deployment | Monitoring | MySQL | Optimization | Prompt engineering | Python | RAG | Redis | Security Compliance | Spring Boot | Vector Database
Education
Bachelor of Engineering | Bachelor of Science | Master of Science
Roles
AI | AI Applications Engineer | Applications Engineer | Backend | Backend Engineer | Engineer
Regions
Countries
States
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