Développeur IA Générative Confirmé (H/F) – RAG, Agents IA & Industrialisation LLMOps
Tasks
- Apply LLMOps best practices
- Build AI agents
- Build conversational assistants
- Collaborate with product owners and stakeholders
- Create embeddings and vector indexes
- Deploy with Docker and Kubernetes
- Design AI microservices and APIs
- Design and develop RAG pipelines
- Develop AI document processing pipelines
- Document system and AI workflows
- Extract information from documents
- Implement AI observability
- Implement OCR and document transformation
- Industrialize solutions with testing
- Integrate LLMs into applications
- Manage model lifecycle and monitoring
- Measure costs errors and hallucinations
- Monitor prompt quality and latency
- Orchestrate multi step tasks
- Perform technical feasibility studies
- Provision infrastructure with Terraform
- Set up CI/CD pipelines
- Set up guardrails for AI outputs
- Version prompts and evaluate models
Perks/Benefits
- N/A
Skills/Tech-stack
AI Governance | AI Search | AWS | AWS Security | Asyncio | Azure | Azure AI | Azure AI Search | CI/CD | CrewAI | Data Governance | Datadog | Docker | Document processing | Elasticsearch | Embeddings | FastAPI | GCP | GDPR | GitHub Actions | GitLab CI | Grafana | Integration Testing | Jenkins | Kubernetes | LLM integration | LLMOps | Langchain | Langfuse | Langgraph | Llamaindex | Microservices | Milvus | Monitoring | OCR | Observability | Pinecone | PostgreSQL | Prometheus | Prompt engineering | Pydantic | Python | Qdrant | RAG | REST APIs | Security Compliance | Semantic Kernel | Terraform | Testing | Unit Testing | Vector Search | Weaviate
Education
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