Azure AI Architect

Aneka Talent Solutions; Redmond; On-site; AUD 257,000 - 343,000; Full time

Job summary

Aneka Talent Solutions seeks an AI Architect to lead enterprise-scale agentic AI initiatives on Azure, combining Foundry, OpenAI, and MA Framework to deliver scalable, secure AI systems.

You will define architectures across data, governance, and MLOps, oversee end-to-end lifecycle, and ensure Responsible AI and observability.

This role emphasizes multi-agent orchestration, knowledge graphs, and enterprise search using Azure AI Search and Fabric.

Qualifications

• Experience architecting enterprise-scale AI solutions on Azure.
• Strong track record delivering multi-agent AI systems and orchestration.
• Expertise in responsible AI practices, governance and security.

Responsibilities

• Architect enterprise-scale Agentic AI solutions using Azure AI Foundry, Azure OpenAI, and MAF.
• Design multi-agent systems and orchestration workflows for autonomous business processes.
• Build advanced RAG, graph-based knowledge mining, and enterprise search with Azure AI Search.
• Define AI/data platform architectures leveraging Fabric, Databricks, and Synapse.
• Oversee full AI/ML lifecycle including deployment, monitoring, MLOps & LLMOps.
• Govern scalable, observable GenAI platforms with strong governance and reliability.
• Define Responsible AI practices and governance across projects.

Skills

Azure AI Foundry

Azure OpenAI Service

MAF

Semantic Kernel

AutoGen

Copilot Studio

Microsoft Fabric

Azure AI Search

Vector databases

Knowledge graphs

MLOps

LLMOps

Responsible AI

Governance

Job description

The AI Architect role should emphasize Azure AI Foundry, Azure OpenAI, Microsoft Agent Framework (MAF), Semantic Kernel, AutoGen, Copilot Studio, Microsoft Fabric, Azure AI Search, MCP, LLMOps, Responsible AI, and enterprise-scale agentic architectures. Also focus on multi-agent orchestration, Azure AI Search, Microsoft Fabric, Entra ID, Purview, Key Vault, MLOps/LLMOps, and governance as core architectural competencies.

Responsibilities

1. Architect and lead enterprise-scale Agentic AI solutions leveraging Azure AI Foundry, Azure OpenAI Service, Microsoft Agent Framework (MAF), Semantic Kernel, AutoGen, and Copilot Studio.

2. Design and implement multi-agent systems, agent orchestration workflows, autonomous business processes, and AI-powered copilots using Microsoft AI technologies.

3. Build and deploy advanced RAG, GraphRAG, Knowledge Mining, and enterprise search solutions using Azure AI Search, vector databases, and knowledge graphs.

4. Define AI and data platform architectures leveraging Microsoft Fabric, Azure Databricks, Azure Data Lake, Synapse Analytics, and Azure Machine Learning.

5. Lead the complete AI/ML lifecycle including:

• Deployment, Monitoring, MLOps & LLMOps

6. Design and govern enterprise GenAI platforms ensuring scalability, reliability, observability, and operational excellence.

7. Define Responsible AI practices include<|endoftext|>