AI Engineer (GenAI & LLM) – Practice IA MARGO
Tasks
- Assess genai use case feasibility
- Build RAG pipelines
- Build evaluation pipelines
- Create CI/CD pipelines
- Deploy LLM solutions
- Design agentic AI architectures
- Develop rag apis
- Implement safety guardrails
- Integrate AI components into applications
- Manage vector indexing
- Monitor latency and costs
- Optimize semantic search
- Orchestrate multi-agent systems
- Perform genai technology research
- Run continuous model evaluation
- Select and fine tune llm models
- Set up llm monitoring
- Track response quality hallucinations relevance
Perks/Benefits
Skills/Tech-stack
API Development | Agent systems | Agentic AI | Arize | Autogen | CI/CD | Docker | Haystack | Kubernetes | Langchain | Langsmith | Language Models | Large Language Models | Llamaindex | MLflow | Milvus | Model Monitoring | Multi-Agent | Multi-Agent Systems | Pinecone | Python | Qdrant | Retrieval-Augmented Generation | Vector Databases | Weaviate
Education
Roles
AI | AI Engineer | Engineer | Learning Engineer | Machine Learning Engineer
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