Project Role : Data Architect
Project Role Description : Define the data requirements and structure for the application. Model and design the application data structure, storage and integration.
Must have skills : Microsoft Azure AI foundry
Good to have skills : Microsoft Azure OpenAI Service, Microsoft BOT Framework
Minimum 7.5 year(s) of experience is required
Educational Qualification : 15 years full time education
Summary:
As an Azure AI Foundry Architect/ Tech Lead, you will lead the design, deployment, and governance of Agentic AI solutions on Microsoft Azure AI Foundry. You will ensure scalable orchestration, observability, and compliance across AI projects while driving innovation in enterprise-grade AI adoption. Acting as a Subject Matter Expert (SME), you will collaborate with multiple teams to deliver secure, efficient, and responsible AI systems, while providing technical leadership and enabling organizational transformation through Microsoft s AI ecosystem.
Roles & Responsibilities:
Serve as the Architect for Microsoft Azure AI Foundry and Agentic AI .
Design and deploy Agentic AI solutions leveraging orchestration, pipelines, and observability in Azure AI Foundry.
Collaborate with data scientists, engineers, architects, and business stakeholders to drive AI adoption.
Ensure AI workloads meet enterprise security, compliance, and governance requirements.
Lead and mentor teams, ensuring accountability and high-quality delivery.
Partner with cross-functional teams to make key architecture and solution design decisions.
Provide scalable solutions for multi-team AI initiatives across the enterprise.
Facilitate workshops and training to upskill teams on Azure AI Foundry, orchestration, and governance.
Monitor solution performance, optimize pipelines, and align outcomes with business goals.
Professional & Technical Skills:
Proven expertise in Microsoft Azure AI Foundry and Agentic AI Architecture (minimum 5 years hands-on experience in Azure AI/ML technologies)
Strong understanding of AI governance, observability, and compliance frameworks.
Experience designing and deploying AI pipelines on Microsoft Azure.
Deep knowledge of Azure ecosystem (Azure Machine Learning, Cognitive Services, OpenAI, Synapse, Logic Apps, etc.).
Ability to analyze large-scale AI workloads and optimize for performance, scalability, and cost-efficiency.
Strong leadership and stakeholder engagement skills.
Familiarity with regulatory requirements for enterprise AI adoption.
Additional Information:
The candidate should have minimum 7 years of experience in Microsoft Azure PaaS, minimum 5 years hands-on experience in Azure AI/ML technologies
A 15 years full time education is required.
15 years full time education
