AI LLM Engineer - Autonomous Network
Tasks
- Add human in the loop approval and confidence scoring
- Build AI agents for fault diagnosis and root cause analysis
- Build RAG frameworks for network operations
- Deploy AI services with Kubernetes and Docker
- Design LLM agent solutions for autonomous network operations
- Develop KPI modelling and predictive analytics
- Develop multi-agent workflows
- Evaluate prompts and retrieval grounding quality
- Implement LLM security prompt injection protection and access controls
- Implement closed loop decision support logic
- Implement vector search and semantic retrieval
- Integrate graph enhanced retrieval and hybrid search
- Optimize AI models for latency cost accuracy and reliability
Perks/Benefits
Skills/Tech-stack
AI Observability | AIOps | APIs | Autogen | ChromaDB | Closed Loop | Closed Loop Triggers | Context Optimization | Data Pipelines | Deep learning | Docker | Embeddings | Fault Correlation | Graph APIs | Graph Databases | KPI Modelling | Knowledge graphs | Kubernetes | Langchain | Langgraph | Language Models | Large Language Models | Llamaindex | MCP | Machine Learning | Milvus | Model Evaluation | Pinecone | Predictive Analytics | Prompt engineering | Python | Qdrant | RAG | Semantic Search | Token optimization | Transformers | Vector Databases | Weaviate
Education
N/A
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