The AI Engineer designs, builds, and operates the core infrastructure and orchestration backbone of AI solutions. This role ensures the platform is secure, scalable, resilient, and production-grade. Key Responsibilities 1. Architect and implement cloud-native AI platforms using Azure. 2. Build and manage agent orchestration services (multi-agent workflows, tool invocation, state management). 3. Knowledge in MCP, A2A and other new protocols 4. Deploy and manage LLM integrations (Azure OpenAI, embeddings, fine-tuned models). 5. Implement RAG pipelines using Azure AI Search, vector databases, and storage. 6. Design secure APIs, authentication, authorization, and secrets management. 7. Support observability: logging, tracing, metrics, and AI performance dashboards. Required Skills & Experience 1. 7+ years in AI, ML - AI Engineer. 2. Deep expertise in Azure (Functions, App Services, Document Intelligence, AI Search, OpenAI). 3. Strong understanding of LLMs, embeddings, RAG, agentic architectures. 4. Proficiency in Python. 5. Experience with infrastructure-as-code (Bicep, Terraform). 6. Strong DevOps and security mindset. 7. Experience with LangGraph, Semantic Kernel, AutoGen, or similar agent frameworks. 8. Knowledge of compliance and data governance for AI systems.
