Senior Developer on Azure AI foundry

Omnix International; Dubai; Presencial; AED 180 000 - 300 000; Tempo integral

Resumo da oferta

Omnix International is seeking a senior AI solutions engineer to design and implement cutting-edge AI workloads on Microsoft Azure. You will build agents, copilots, and retrieval-augmented generation systems integrated with enterprise apps and data stores.

You will apply prompt engineering, model evaluation and secure access practices, while deploying workloads with AKS or App Service. Strong cloud and security fundamentals are essential.

Qualificações

• Experience designing and developing solutions on Microsoft Azure.
• Hands-on with Azure AI Foundry or Azure OpenAI platforms.
• Strong Microsoft stack development for AI applications and automation.

Responsabilidades

• Design and develop generative AI solutions using Azure AI Foundry and Azure OpenAI.
• Build AI agents, copilots, conversational apps and retrieval-augmented generation solutions.
• Develop and integrate backend services, APIs and automation components using CoPilot stack.
• Integrate AI solutions with enterprise applications, databases, document repositories and business systems.
• Configure and use Azure AI Search, vector search, embeddings and document-processing services.
• Implement prompt engineering, model selection, evaluation and response-quality testing.

Conhecimentos

Azure AI Foundry

Azure OpenAI

PowerPlatform

REST APIs

CI/CD

Containerization

RBAC / IAM

Azure DevOps

Ferramentas

Azure Kubernetes Service

LangChain

LangGraph

IBM WebMethods

Descrição da oferta de emprego

Key Responsibilities

• Design and develop generative AI solutions using Azure AI Foundry and Azure OpenAI.
• Build AI agents, copilots, conversational applications and retrieval-augmented generation solutions.
• Develop and integrate backend services, APIs and automation components using CoPilot stack.
• Integrate AI solutions with enterprise applications, databases, document repositories and business systems.
• Configure and use Azure AI Search, vector search, embeddings and document-processing services.
• Implement prompt engineering, model selection, model evaluation and response-quality testing.
• Develop orchestration workflows using Microsoft Agent Framework, Semantic Kernel or equivalent frameworks.
• Deploy AI workloads using Azure Functions, App Service, Container Apps, AKS or other suitable Azure services.
• Implement secure access using Microsoft Entra ID, managed identities, RBAC and Azure Key Vault.
• Establish CI/CD pipelines using Azure DevOps or GitHub Actions.
• Implement monitoring, logging, tracing, content safety and responsible AI controls.
• Support performance optimization, cost management, troubleshooting and production readiness.
• Produce technical documentation, deployment guides and knowledge-transfer materials.

Required Skills and Experience

• Practical experience designing and developing solutions on Microsoft Azure.
• Hands-on experience with Azure AI Foundry, Azure OpenAI or equivalent generative AI platforms.
• Strong Microsoft stack using PowerPlatform development experience for AI applications, integrations and automation.
• Experience building REST APIs and integrating cloud services and enterprise applications.
• Understanding of large language models, prompt engineering, embeddings, vector databases and retrieval-augmented generation.
• Experience with Azure AI Search, Azure Storage and relevant Azure application services.
• Familiarity with containerization, Git-based development and CI/CD practices.
• Understanding of Azure security, networking, identity and access-management principles.
• Strong troubleshooting, documentation and stakeholder-communication skills.

Desirable Skills

• Experience with Microsoft Agent Framework, Semantic Kernel, LangChain or LangGraph.
• Experience with Java, C#, .NET, IBM WebMethods for integration with enterprise applications.
• Experience with Azure AI Components namely Azure Machine Learning, Document Intelligence, Cosmos DB or Microsoft Fabric.
• Knowledge of model evaluation, observability, responsible AI and AI governance.
• Experience deploying workloads on Azure Kubernetes Service or Azure Container Apps.
• Familiarity with DevOps, MLOps and LLMOps practices.

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