AI Solution Architect

What You Will Do

• 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.

What We Are Looking For

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.

• Proficiency 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:

• Low-code vs pro-code approaches.

• Copilot Studio vs custom AI solutions.

• Single-agent vs multi-agent architectures.

• Human-in-the-Loop vs autonomous workflows.

• Trade-offs between speed scalability security and cost.

Soft Skills

• Excellent communication and stakeholder management skills.

• Ability to communicate effectively with both technical and business audiences.

• Fluent written and spoken English.