AI Solution Architect

This role specializes in architecting intelligent, enterprise-grade AI solutions that harness the full power of modern AI platforms including Azure AI Foundry, Azure OpenAI, Microsoft Copilot, and open-source AI frameworks such as LangChain and Semantic Kernel. You will design secure, scalable, and production-ready AI systems that automate complex workflows, reason over enterprise data, and power next-generation agent and generative AI experiences.

As an AI Solution Architect in the Data & AI Solutions Team, you will serve as a trusted technical advisor and innovation leader partnering with business stakeholders to modernize legacy processes, design AI-augmented digital experiences, and define governance guardrails for responsible AI adoption at scale. You will play a pivotal role in presales and solutioning, co-creating compelling solution narratives, proposals, and prototypes that win client confidence and accelerate deal cycles.

You will also co-create and maintain a library of AI solution offerings including reference architectures, reusable AI components, and governance toolkits that enable repeatable and scalable delivery of Data & AI use cases across the enterprise.

What you'll do

• Lead envisioning and discovery workshops to identify opportunities where generative AI, agentic frameworks, and LLMs can streamline workflows, augment decisions, and enable transformative AI-driven experiences.
• Architect end-to-end intelligent AI systems using Azure AI Foundry, Azure OpenAI Service, and Microsoft Copilot spanning model selection, orchestration, grounding, and deployment.
• Design agentic AI experiences using frameworks such as LangChain, Semantic Kernel, and AutoGen including multi-agent orchestration, tool/function calling, memory management, and feedback loops.
• Define AI solution patterns including Retrieval-Augmented Generation (RAG), fine-tuning strategies, prompt engineering, and responsible AI guardrails (content filtering, safety rails, hallucination mitigation).
• Design enterprise integration architectures connecting AI services with Microsoft 365, Dynamics 365, Azure data platforms, and third-party systems via APIs, event-driven patterns, and custom connectors.
• Define AI governance frameworks including model lifecycle management, data access controls, compliance alignment, audit logging, and responsible AI policies ensuring solutions are secure, explainable, and trustworthy.
• Develop reusable AI components, reference architectures, and solution templates that accelerate delivery of common generative AI, copilot, and agentic patterns across clients and engagements.
• Build and deliver compelling prototypes, proof-of-concepts (POCs), and demos that showcase AI-driven business scenarios translating complex AI capabilities into clear, tangible business value for client stakeholders.
• Support sales and account teams with solutioning, estimates, prototypes, and demos that showcase AI-driven business scenarios on Power Platform.
• Coach and review AI solutions built by engineering teams, with emphasis on responsible AI usage, security best practices, prompt design, and solution quality.
• Guide delivery teams through implementation, including design of AI interactions, telemetry/feedback loops, and risk/issue management for LLM-based solutions.
• Monitor AI solution performance, usage patterns, and model behavior recommending improvements to standards, patterns, and enablement programs to drive continuous improvement.

What you'll need to succeed

• 7+ years of experience in solution architecture, AI/data engineering, or technology consulting with at least 3+ years delivering production AI or generative AI solutions in enterprise environments.
• Hands-on expertise with Azure AI Foundry including model catalog, prompt flow, evaluation pipelines, fine-tuning, and AI deployment patterns.
• Deep experience with Azure OpenAI Service including GPT model families, embedding models, prompt engineering, function calling, and responsible AI configuration.
• Proven ability to design and build agentic AI systems using frameworks such as LangChain, Semantic Kernel, or AutoGen including multi-agent patterns, tool use, memory, and orchestration.
• Strong experience designing and implementing RAG architectures using Azure AI Search, vector databases (e.g., Pinecone, Qdrant, pgvector), and enterprise data sources.
• Proficiency with Microsoft Copilot ecosystem - including Copilot Studio, Microsoft 365 Copilot extensibility, and custom copilot design for enterprise use cases.
• Nice to have: Foundational understanding of data platform concepts (warehouses, lakehouses, data products) and how they feed AI and copilot scenarios.
• Strong communication and facilitation skills, with the ability to explain no-code / low-code / pro-code and AI trade-offs to both IT and business stakeholders.
• Prior consulting or solution architecture experience, including workshops, POCs, and supporting complex deal cycles, is highly desirable.