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Evnek Technologies Pvt Ltd

Azure AI Architect

Posted 2 days ago
10+ years experience
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AI Summary

The Azure AI Architect will review, optimize, and accelerate existing Microsoft Foundry deployments while designing secure integrations with enterprise data sources. They will also provide technical guidance to engineering teams and evaluate AI solution performance regarding quality, latency, and costs.

Job Description: Azure AI Architect

Location: Remote
Experience: 10+ Years
Notice Period: Immediate Joiners Only

Job Overview

We are looking for a highly experienced, hands-on Azure AI Architect to support an enterprise client in reviewing, optimizing, and accelerating its existing Microsoft Foundry deployment.

The ideal candidate should have strong expertise in Microsoft Azure architecture, Microsoft Foundry, Retrieval-Augmented Generation (RAG), and enterprise security, along with the ability to work directly with client technical leads, infrastructure teams, security teams, and AI engineers.

Key Responsibilities

  • Review the existing Microsoft Foundry architecture and private connectivity setup, identify technical gaps, and recommend practical improvements.
  • Design and validate secure integration between Microsoft Foundry and enterprise data sources, including on-premises SQL databases, ERP systems, and internal documents.
  • Implement conversational AI solutions using appropriate Microsoft Azure services and Azure AI Search.
  • Design and optimize RAG-based solutions for enterprise document retrieval and contextual responses.
  • Assess identity management, access controls, network security, and connectivity between cloud and on-premises environments.
  • Validate key Azure configurations and integration approaches through hands-on implementation and troubleshooting.
  • Evaluate suitable Microsoft technologies, including Microsoft Foundry agents, Azure AI Search, and Copilot Studio, based on business and technical requirements.
  • Document architecture decisions, technical dependencies, risks, and a phased implementation roadmap.
  • Collaborate with client technical leads and engineering teams to prioritize improvements and accelerate deployment.
  • Provide technical guidance, knowledge transfer, and implementation recommendations to the client's engineering team.
  • Evaluate AI solution performance, including answer quality, response latency, reliability, and token consumption costs.


Preferred Skills

  • Experience working in GCC High or similarly regulated and controlled enterprise environments.
  • Familiarity with Microsoft Bicep and Infrastructure as Code (IaC).
  • Hands-on experience with Microsoft Foundry agents and Copilot Studio.
  • Experience evaluating and optimizing AI response quality, latency, reliability, and token costs.
  • Knowledge of Microsoft Azure security configurations, service availability, and access restrictions in controlled environments.
  • Experience creating architecture diagrams, technical assessments, implementation plans, and deployment recommendations.

Requirements

Required Skills and Experience

  • 10+ years of overall experience in IT, enterprise architecture, cloud architecture, or related technical roles.
  • Strong, hands-on experience designing, configuring, and deploying Microsoft Foundry (formerly Azure AI Foundry) solutions.
  • Extensive experience with Microsoft Azure architecture and enterprise cloud integrations.
  • Strong understanding of corporate networking, private connectivity, identity and access management, and secure cloud-to-on-premises integration.
  • Hands-on experience integrating AI applications with SQL databases, ERP systems, and enterprise document repositories.
  • Strong expertise in Retrieval-Augmented Generation (RAG), conversational AI, and enterprise knowledge retrieval.
  • Experience with Azure AI Search, including indexing, retrieval strategies, and integration with AI applications.
  • Ability to assess existing architectures, identify gaps, troubleshoot complex technical issues, and recommend scalable solutions.
  • Understanding of enterprise security, data access controls, and secure handling of internal business data.
  • Excellent communication, stakeholder management, technical documentation, and knowledge-transfer skills.
  • Ability to work independently and collaborate effectively with infrastructure, security, and AI engineering teams.




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