AI Solution Architect

Insight Global; Atlanta (GA); On-site; USD 140,000 - 200,000; Full time

Job summary

Insight Global is seeking an AI Solution Architect to lead the design of enterprise AI solutions leveraging Azure AI Foundry, Azure OpenAI Service, and Copilot ecosystems. You will partner with stakeholders to modernize processes and define governance guardrails for responsible AI adoption at scale.

You will co-create reference architectures, reusable AI components, and prototypes, and support sales with solutioning and POCs that translate complex AI capabilities into tangible business value for

Qualifications

• 7+ years of experience in solution architecture, AI/data engineering, or technology consulting.
• 3+ years delivering production AI or generative AI solutions in enterprise environments.
• Hands-on experience with Azure AI Foundry and Azure OpenAI Service.
• Experience with LangChain, Semantic Kernel or AutoGen for agentic AI.

Responsibilities

• Lead envisioning and discovery workshops to identify AI opportunities.
• Architect end-to-end intelligent AI systems on Azure platforms.
• Design agentic AI experiences with multi-agent orchestration and tool use.
• Develop reusable AI components and reference architectures.
• Support sales with solutioning, prototypes, and demos.
• Coach delivery teams on responsible AI and security best practices.
• Define AI governance frameworks and data access controls.

Skills

Azure AI Foundry

Azure OpenAI Service

LangChain

Semantic Kernel

AutoGen

RAG architectures

Multi-agent patterns

Prompt engineering

Governance and security

Solution architecture

Tools

Pinecone

Qdrant

pgvector

Power Platform

Job description

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.