AI Solution Architect

Job Description & Summary The Opportunity   We are looking for an   AI Solution Architect   to join the   CEE IT Digital Solutions team   and lead the design of enterprise AI solutions across the Microsoft ecosystem.   You will define architecture standards, engineering best practices, and reusable delivery patterns that enable teams to build secure, scalable, maintainable, and cost-effective AI solutions. Working closely   with various people from   developers, business analysts, project managers, security teams,   to   business stakeholders, you will help shape technology decisions and accelerate AI adoption across the organization.   This is a hands-on role requiring   expertise   across the full AI spectrum, from low-code solutions built with   Copilot Studio and Power Platform   to enterprise-grade AI applications built on   Azure AI services and modern AI frameworks . You will help   determine   the right architecture, technology stack, and delivery approach for each business scenario.

Define AI standards, reference architectures, and reusable design patterns that accelerate consistent, high-quality solution delivery.   Design scalable, secure, and cost-efficient AI architectures and integration strategies.   Design enterprise AI solutions and agentic architectures, including RAG capabilities, voice-based agents, intelligent automation, multi-agent systems, orchestration patterns, and Human-in-the-Loop processes.   Guide architecture decisions across Microsoft AI technologies such as Copilot Studio, Azure AI Foundry, Azure OpenAI, and modern AI development frameworks.   Remain hands-on through prototyping, proof-of-concepts, technical reviews, and key implementation decisions, defining approaches for MVP delivery, production deployment, and solution scaling.   Define AI testing, evaluation, monitoring, quality assurance, and success measurement approaches.   Collaborate with governance, security, and risk teams to ensure compliance with enterprise standards and responsible AI requirements.   Support solution shaping, technology selection, effort estimation, and technology adoption decisions, including evaluation of emerging AI capabilities and platforms.   Mentor team members and help grow AI engineering capability across the organization.

Required Experience   8+ years of experience in software engineering, solution architecture, or enterprise application development.   4+ years of experience designing and delivering AI, GenAI, intelligent automation, or machine learning solutions.   Strong experience with Copilot Studio, Microsoft Foundry, Azure OpenAI, and Azure AI Search.   Strong understanding of Copilot Studio and enterprise AI solution design.   Solid   experience with the Azure platform, including application hosting, integration, security, identity, networking, storage, and data services.   P roficiency   in Python   or other programming   languages   and experience with modern software development practices.   Experience designing and integrating REST APIs and enterprise applications.   Hands-on experience with SQL and relational databases.   Experience with GitHub and source control best practices.   Strong understanding of LLMs, Generative AI, prompt engineering, vector search, embeddings, and RAG architectures.   Experience with agent-based architectures, orchestration frameworks, and Human-in-the-Loop solutions.   Knowledge of AI evaluation methods, quality measurements, monitoring, and observability practices.   Understanding of Responsible AI, AI governance, and AI cost optimization principles.   Strong understanding of AI-assisted software development practices, including the effective use of tools such as M365 Copilot, Cursor AI, Claude Code, and similar AI-powered engineering assistants.   Decision-Making Capabilities   You should be comfortable making architecture decisions across: