Senior AI Architect – Azure & Cloud AI

Role Overview

We are seeking an AI Architect to join our growing AI practice on a high-visibility enterprise engagement. This is a senior, client-facing role where you will provide thought leadership and define the technical direction across a complex, multi-workstream AI program.

What You'll Do

• Thought Leadership & Technical Direction
• Serve as the senior technical voice on the engagement, setting the architectural vision and ensuring consistency across workstreams
• Define and govern end-to-end Azure AI architecture spanning Azure OpenAI, Azure Machine Learning, and enterprise data platforms
• Develop reference architectures, patterns, and reusable assets that accelerate delivery and elevate the practice
• Mentor and upskill team members on Azure AI best practices, design patterns, and emerging capabilities
• Client Engagement & Solution Architecture
• Lead architecture design sessions and workshops with client stakeholders to align on strategy and technical approach
• Translate complex business requirements into scalable, secure, and maintainable AI-powered solutions
• Map AI use cases to measurable business value, ensuring enterprise standards and governance are embedded from the start
• Present architectural recommendations with clarity and confidence to both technical and executive audiences
• Technical Delivery
• Arcitect and oversee implementation of AI solutions across Azure OpenAI, Azure ML, and supporting data infrastructure
• Establish design standards for model deployment, prompt engineering, data integration, and AI observability
• Establish a scalable operating model for AI industrialization by standardizing deployment, monitoring, governance, and support processes across existing AI solutions to improve reliability, reuse, and speed to value
• Leverage Model Context Protocols (MCPs) to enable secure, modular integration between agents, enterprise systems, and data sources, creating a more interoperable and extensible agentic AI ecosystem
• Implement orchestration and guardrail frameworks for agentic workflows to ensure AI agents can collaborate effectively, access the right contextual information, and operate with appropriate oversight, auditability, and human-in-the-loop controls
• Ensure all solutions adhere to enterprise security, compliance, and reliability requirements
• Collaborate closely with data, engineering, and business teams to ensure successful end-to-end delivery

Preferred Education & Technical Expertise

• Master's Degree Required
• 8+ years of experience leading the implementation of enterprise-grade AI and agentic AI solutions across cloud and hybrid environments
• Design scalable AI platforms leveraging Azure and AWS services, including secure model deployment, orchestration, monitoring, and governance
• Build and operationalize LLM-powered applications using frameworks such as LangChain and LangGraph
• Define agentic architectures including multi-agent orchestration, tool calling, memory management, MCP integration patterns, and human-in-the-loop controls
• Establish best practices for AI industrialization, including CI/CD, model lifecycle management, observability, prompt/version management, evaluation frameworks, and guardrails
• Integrate AI systems with enterprise applications, APIs, vector databases, workflow platforms, and operational systems
• Collaborate with business, data, security, and engineering teams to translate business requirements into scalable AI architectures
• Provide technical leadership across architecture reviews, platform strategy, vendor selection, and AI governance initiatives

Preferred Skills

• Familiarity with agentic AI frameworks (e.g., LangChain, AutoGen, Semantic Kernel) and RAG architectures
• Experience with Azure data services including Azure Synapse, Azure Data Factory, or Microsoft Fabric
• Knowledge of AI governance, responsible AI practices, and enterprise security considerations
• Azure certifications (e.g., Azure Solutions Architect Expert, Azure AI Engineer Associate)