Job Description
AI Infrastructure Engineer As an AI Infrastructure Engineer, you will play a pivotal role in developing and maintaining the core infrastructure that powers our AI systems. Your work will directly impact the stability, scalability, and efficiency of our AI services.
Key Responsibilities
- Continuously develop and upgrade architecture team's core services (API gateways, service registration/discovery, load balancing) to ensure system stability and scalability
- Optimize AI infrastructure engineering: reduce AI call latency, improve user experience; lower costs through caching, routing strategies, model selection; ensure AI infrastructure stability
- Develop DevOps solutions tailored for AI teams to enhance delivery efficiency
- Establish AI capability evaluation and monitoring systems to track model call costs, effectiveness, and performance
- Build and introduce company-wide AI technical infrastructure including shared development tools, code libraries, and middleware to improve R&D efficiency
- Promote AI implementation to boost R&D efficiency (code generation, intelligent testing, smart operations, fault diagnosis, etc.)
- Establish technical standards and specifications (including AI engineering guidelines) to drive technical implementation and ensure code quality/system performance
- Enhance R&D efficiency by optimizing development processes and promoting technical cost optimization/resource utilization
- Tackle technical challenges, solve system bottlenecks, and provide innovative solutions
- Demonstrate strong communication skills and teamwork to drive cross-team implementation of technical requirements
- Mentor team members for technical growth and organize knowledge sharing sessions
Job Requirements
- Education: Bachelor's degree or above in Computer Science or related field
- Experience: 5+ years of backend development experience
- Programming Languages: Proficient in at least one of Go, Java, or C++
- Tools: Skilled in one or more programming tools like Cursor/Claude Code/Codex
- Cloud Services:
- Deep understanding of at least one major cloud provider (Alibaba Cloud/AWS/Google Cloud)
- Familiar with cloud AI services (e.g., Alibaba Cloud Bailian/Open Router) integration
- Experience in cloud architecture design, deployment, and operations
- Engineering Capabilities:
- Hands-on experience with distributed system design and high-concurrency systems
- Familiar with middleware like message queues (Kafka/RocketMQ), caching (Redis), vector databases (Milvus/Pinecone)
- Strong coding standards and system design capabilities
- LLM Application Experience:
- Knowledgeable about mainstream LLM application paradigms (Prompt, RAG, Agent, Function Calling, Memory)
- Practical experience implementing RAG systems or Agent applications
- Preferred Qualifications:
- Experience with model fine-tuning (LoRA, QLoRA) or model deployment
- Knowledge of Web3/blockchain, experience with financial/trading systems
- Contributions or technical influence in AI open-source communities
Benefits
Please contact our HR directly via Telegram for benefits information!
