AI Engineer
AED 144K-192K (estimate) Senior-level Full Time
Tasks
- Analyze performance metrics and improve quality
- Apply MLOps and LLMOps best practices
- Build Agentic AI workflows
- Build backend services and APIs
- Design develop deploy GenAI solutions
- Design hybrid search architectures
- Detect data quality anomalies
- Develop interactive React interfaces for AI insights
- Develop secure scalable services on Azure
- Implement AI guardrails and output validation
- Implement automated data quality checks
- Implement identity and access management integration
- Implement rag pipelines
- Implement tool calling and function execution
- Integrate React with AI ML services
- Manage agent memory
- Monitor log trace and observe AI systems
- Optimize prompts retrieval and agent flows
- Orchestrate multi-agent systems
- Perform end-to-end data validation
- Set up model prompt and retrieval testing
Perks/Benefits
- N/A
Skills/Tech-stack
AI Search | API Management | App Services | Azure AI | Azure AI Search | Azure App | Azure App Services | Azure Bot | Azure Bot Framework | Azure Bot Service | Azure Cache | Azure Cache for Redis | Azure Data | Azure Data Factory | Azure Databricks | Azure Document Intelligence | Azure Functions | Azure Kubernetes | Azure Kubernetes Service | Azure OpenAI | Bot Framework | CI/CD | Context engineering | Data Factory | Databricks Vector Search | DevOps | Document Intelligence | Embeddings | Entra ID | FastAPI | Flask | Graph Databases | Guardrails | Hallucination control | Haystack | JavaScript | Kubernetes Service | LLM Evaluation | LLMOps | Langchain | Langgraph | MLOps | Microsoft Copilot | Microsoft Entra | Microsoft Entra ID | N8n | Neo4j | Prompt engineering | PyTorch | Python | RAG | React | SQL | Spark | TensorFlow | Transformers | TypeScript | Vector Databases | Vector Search
Education
N/A
Roles
AI | AI Engineer | Developer | Engineer | Full Stack | Full Stack Developer | Stack Developer
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