Data and AI Architect

Roles and Responsibilities :

• Define the reference architecture, standards, and target-state roadmap for the enterprise Data & AI platform.
• Lead architecture design for data products, AI applications, and AI agents, including model selection, grounding patterns, tool integration, orchestration, and lifecycle controls.
• Design integration patterns across Microsoft 365, Power Platform, Dataverse, ERP, CRM, HR, ITSM, APIs, and custom Azure services.
• Establish design guardrails for security, privacy, identity, DLP, observability, resilience, and scalability across the platform.
• Guide solution teams on when to use Fabric, Foundry, Copilot Studio, Power Automate, or custom Azure components based on business and technology requirements.
• Facilitate architecture workshops, design reviews, and key decision forums with engineering, business, governance, and security stakeholders.
• Mentor engineering and product teams and contribute to reusable architecture assets, patterns, and standards.

Skills:

• Strong architecture experience across Azure cloud, enterprise integration, and data platform design.
• Deep understanding of Microsoft Fabric and modern data platform patterns for ingestion, storage, serving, and governance.
• Hands-on understanding of Microsoft Foundry capabilities for AI applications and agents, including evaluation, monitoring, and lifecycle considerations.
• Hands-on understanding of Copilot Studio, including connectors, actions, topics, orchestration patterns, and enterprise deployment considerations.
• Strong knowledge of security, identity, access management, compliance, and operational governance in enterprise Azure environments.
• Excellent stakeholder engagement, workshop facilitation, and documentation skills, with the ability to create clear and actionable design decision.

Experience:

• Minimum 5–7+ years of architecture experience in Azure-based enterprise environments.
• Demonstrated experience defining target architectures, reference patterns, or solution standards for complex platforms.
• Experience working with both business stakeholders and engineering teams to translate use cases into scalable platform decisions.
• Prior experience with AI platform architecture, agent architecture, or enterprise copilot design is strongly preferred.