Overview Our client in the consulting space is seeking a Senior Consultant – Azure GenAI Backend Engineer to design and implement scalable Generative AI solutions with a strong focus on RAG architectures and Azure-native serverless platforms. This role requires deep expertise in Azure AI services, backend system design, authentication mechanisms, and cloud-native architecture to deliver secure, production-grade AI systems. Key Responsibilities - Design and implement RAG-based architectures using Azure OpenAI and Azure AI Search. - Develop backend APIs and services to support GenAI applications. - Architect and deploy Azure serverless solutions (Azure Functions, Logic Apps, Container Apps). - Build scalable data pipelines for indexing, embedding, and retrieval workflows. - Implement CI/CD pipelines for AI systems using Azure DevOps or GitHub Actions. - Define and implement system architecture ensuring performance, scalability, and high availability. - Apply infrastructure as code using Terraform or Bicep. - Collaborate with frontend, data, and AI teams to deliver end-to-end GenAI solutions. - Enforce security, governance, and compliance best practices. Required Skills & Experience Core GenAI & Architecture - Hands-on experience building RAG solutions in production. - Strong understanding of LLMs, embeddings, vector search, prompt engineering. - Experience with Azure AI Search and Azure OpenAI. - Knowledge of agentic workflows (preferred). Azure & Cloud - Strong experience with: - Azure Functions - Azure Container Apps - Azure App Services - Azure Storage & Key Vault - Solid understanding of Azure networking & identity management. - Experience designing serverless architectures. Backend Development - Strong proficiency in Python, Java or http://node.js. - REST API development and microservices. - Strong system design capabilities. DevOps - CI/CD pipelines (Azure DevOps / GitHub Actions). - Docker & Kubernetes (good to have). - Infrastructure as Code (Terraform / Bicep). Nice to Have - AWS exposure. - Consulting experience. - Experience deploying AI systems in regulated environments.