Azure AI Architect

Accountabilities

Review existing Microsoft Foundry architectures and private connectivity configurations, identify technical gaps, and recommend practical improvements to accelerate deployment.
Design and validate secure integrations between Microsoft Foundry and enterprise data sources, including on-premises SQL databases, ERP systems, and internal document repositories.
Architect, implement, and optimize conversational AI solutions using appropriate Microsoft Azure services and Azure AI Search.
Design and enhance Retrieval-Augmented Generation (RAG) solutions to support accurate enterprise document retrieval, contextual understanding, and relevant AI-generated responses.
Assess and strengthen identity management, access controls, network security, and connectivity between cloud and on-premises environments.
Validate Azure configurations and integration approaches through hands-on implementation, testing, troubleshooting, and technical assessment.
Evaluate and recommend suitable Microsoft technologies, including Microsoft Foundry agents, Azure AI Search, and Copilot Studio, based on business requirements, technical constraints, and architectural objectives.
Assess AI solution performance across key metrics, including response quality, latency, reliability, and token consumption costs, and implement improvements where necessary.
Document architecture decisions, technical dependencies, identified risks, and recommended solutions, including a phased implementation and deployment roadmap.
Collaborate with client technical leads, infrastructure teams, security specialists, and AI engineers to prioritize improvements and resolve complex technical challenges.
Provide technical guidance, knowledge transfer, and implementation recommendations to support the client's engineering team in adopting and maintaining AI solutions.
Promote secure, scalable, and maintainable architecture practices aligned with enterprise standards and operational requirements.
Requirements
10+ years of overall professional experience in IT, enterprise architecture, cloud architecture, or related technical roles.
Extensive hands-on experience designing, configuring, deploying, and optimizing Microsoft Foundry solutions, formerly known as Azure AI Foundry.
Strong expertise in Microsoft Azure architecture, cloud infrastructure, and enterprise application integrations.
Deep understanding of enterprise networking, private connectivity, identity and access management, and secure cloud-to-on-premises integration.
Practical experience integrating AI applications with SQL databases, ERP systems, and enterprise document repositories.
Strong knowledge of Retrieval-Augmented Generation (RAG), conversational AI, and enterprise knowledge retrieval architectures.
Hands-on experience with Azure AI Search, including indexing strategies, information retrieval, and integration with AI-powered applications.
Experience evaluating existing architectures, identifying design gaps, troubleshooting complex technical issues, and developing scalable, secure solutions.
Understanding of enterprise security principles, data access controls, and the secure handling of confidential internal business information.
Strong communication and stakeholder management skills, with the ability to work directly with client technical leads and cross-functional engineering teams.
Proven ability to produce clear architecture diagrams, technical assessments, implementation plans, and deployment recommendations.
Excellent documentation and knowledge-transfer capabilities, with a collaborative approach to supporting engineering teams.
Ability to work independently, prioritize technical activities, and deliver practical solutions in a client-facing environment.
Preferred: Experience working in GCC High or similarly regulated and tightly controlled enterprise environments.
Preferred: Familiarity with Microsoft Bicep and Infrastructure as Code (IaC) practices.
Preferred: Hands-on experience with Microsoft Foundry agents and Copilot Studio.
Preferred: Experience measuring and optimizing AI response quality, latency, reliability, and token consumption costs.
Preferred: Knowledge of Azure security configurations, service availability, and access restrictions in controlled environments.
Availability: Immediate joiners only, as specified in the original job posting.
Benefits
Fully remote work arrangement, offering flexibility in where you work within the applicable employment and contract arrangements.
Contract-based engagement with opportunities to contribute to enterprise-scale AI architecture and implementation initiatives.
Hands-on exposure to Microsoft Foundry, Azure AI Search, RAG architectures, conversational AI, and other enterprise AI technologies.
Opportunity to solve complex cloud architecture, security, and data integration challenges for an enterprise client.
Collaboration with technical leads, infrastructure specialists, security teams, and AI engineering professionals.
Opportunity to influence architectural decisions, improve AI application performance, and accelerate enterprise AI adoption.
Professional growth through practical experience with emerging AI capabilities, cloud security, and advanced enterprise integration patterns.