AI Cloud Architect

Freeman Mathis & Gary, LLP is a national law firm in a period of continued growth and modernization. As the firm expands, we are investing in the infrastructure needed to support secure, practical, and well‑governed use of artificial intelligence across the firm. The Azure AI Platform Architect will help establish the technical foundation for FMG’s AI platform on Microsoft Azure, including the architecture, administration, security models, deployment patterns, and operational standards needed to support enterprise AI systems. The right candidate will have the opportunity to help shape how AI infrastructure is built and governed inside a growing law firm. This role is well‑suited for someone who enjoys building from the ground up, creating reusable patterns, solving infrastructure bottlenecks, and helping technical teams move from concept to production in a secure and disciplined way. Azure AI Platform Architect is responsible for designing, deploying, and governing the firm’s AI platform on Microsoft Azure. This role combines enterprise architecture with hands‑on Azure administration to ensure AI systems are secure, scalable, and operationally reliable. The Azure AI Platform Architect establishes the technical foundation for AI services, enabling knowledge systems, automation workflows, and AI applications to operate safely within the firm’s infrastructure. This role works closely with the Director of Knowledge Management , automation engineers, AI engineers, and related firm stakeholders to translate business and knowledge requirements into production‑ready AI infrastructure. The legal environment is fast‑paced and deadline‑driven, so working with a sense of urgency is important. Ideal candidates are highly technical, collaborative, security‑minded, and able to quickly learn and adapt to new systems, services, and platform requirements. Reports to: Chief Innovation Officer Job Responsibilities and Essential Duties Design and maintain the Azure architecture supporting enterprise AI workloads. Establish reference architectures for AI solutions. Apply Azure Well‑Architected Framework principles to AI platform design. Build scalable, production‑grade AI environments. Create and maintain platform architecture diagrams, infrastructure standards, and deployment patterns for AI systems. Deploy and manage Azure services used for AI development. Work with Azure AI technologies and related services, including Azure Machine Learning, where appropriate; Logic Apps; Container services. Understand Azure service quotas, usage limits, and scaling constraints. Design architectures that are resilient to service failures. Manage cost and resource utilization for AI‑related Azure services. Provide Azure administration support sufficient to ensure rapid development and operational stability. Manage Azure subscriptions and resource groups. Structure development, testing, and production environments. Configure Microsoft Entra ID access controls. Manage service principals and managed identities. Monitor usage quotas and cost controls. Enable AI development teams to operate without unnecessary infrastructure bottlenecks. Ensure AI systems meet enterprise security and governance requirements. Implement least‑privilege identity models. Support logging and auditability for AI systems. Support compliance with confidentiality standards. Support responsible AI principles, including human‑in‑the‑loop design and monitoring. Ensure the AI platform operates reliably in production. Monitor AI services and system performance. Troubleshoot infrastructure issues. Ensure operational readiness for AI systems. Assist with special projects and additional duties as assigned. Collaboration with Other Roles This role operates at the platform layer and collaborates with the following roles. Director of Knowledge Management Focus: Knowledge governance and content lifecycle. Interaction: Translate knowledge management requirements into platform capabilities. Ensure the infrastructure supports knowledge retrieval systems. Coordinate on data access and governance policies. Boundary: The Azure AI Platform Architect does not define knowledge taxonomies or ontologies. Knowledge Systems Architect Focus: Ontology, taxonomy, and semantic knowledge models. Interaction: Implement infrastructure needed for semantic search. Support knowledge graph and retrieval systems. Boundary: The Azure AI Platform Architect provides infrastructure and platform design, while the Knowledge Systems Architect defines knowledge structure and semantic models. Automation Engineers Focus: Workflow automation and system integration. Interaction: Provide APIs and infrastructure needed for automation. Enable secure integration between AI services and workflow systems. Support deployment of automation services. Boundary: Automation engineers design workflows; the Azure AI Platform Architect ensures the platform can support them securely and reliably. AI Engineers Focus: Building AI applications. Interaction: Manage access to AI services. Support model deployment and scaling. Boundary: AI engineers build applications; the Azure AI Platform Architect ensures those applications run on a secure, scalable platform. Innovation Governance / AI Governance Focus: Policy and risk management. Interaction: Implement governance controls within Azure architecture. Enforce security and access standards. Support auditability and compliance. Boundary: Governance defines policies; the Azure AI Platform Architect implements them technically. Decision Authority The Azure AI Platform Architect has authority over: Infrastructure security models Service configuration and scaling patterns Decisions about knowledge structure, legal workflows, or AI product features remain with their respective domain leads. Requirements Strong knowledge of Microsoft Azure architecture and administration. Ability to design and maintain Azure architecture supporting enterprise AI workloads. Experience deploying and managing Azure services used for AI development. Understanding of Azure service quotas, scaling limits, resiliency considerations, and cost/resource utilization. Experience managing Azure subscriptions, resource groups, and environment structures. Experience configuring Microsoft Entra ID access controls. Experience managing service principals, managed identities, and least‑privilege access models. Strong knowledge of cloud security and identity systems. Ability to support logging, auditability, confidentiality standards, and governance requirements. Ability to monitor AI services and system performance. Ability to troubleshoot infrastructure issues and support deployment pipelines. Strong written and verbal communication skills. Ability to work with and maintain confidential and sensitive information. Ability to work in a fast‑paced environment with strict deadlines. Ability to learn quickly and adapt to new systems, tools, and processes. Collaborative and professional demeanor when working with technical and non‑technical stakeholders. Education and Experience Bachelor’s degree required; degree in Computer Science, Information Systems, Engineering, Data Science, Cybersecurity, or a related technical field preferred. 7–12 years of experience in cloud architecture or related technical roles. Significant experience designing production workloads on Microsoft Azure. Strong knowledge of cloud security and identity systems. Experience with Azure OpenAI, Azure AI Search, Azure Machine Learning, Azure Functions, Logic Apps, or container services preferred. Preferred Certifications Microsoft Certified: Azure Solutions Architect Expert Success Metrics — First 12 Months The successful candidate will: Establish a secure Azure AI platform. Enable the firm’s first enterprise AI applications. Support knowledge retrieval infrastructure. Benefits At FMG, people are our greatest asset. We invest in your success and well‑being through: Competitive compensation Medical, dental, and vision coverage HSA and FSA options 401(k) with 3% employer Safe Harbor contribution Generous PTO and work‑life balance Year‑end bonuses and referral programs Firm‑paid life insurance and long‑term disability Employee Assistance Program A collaborative, respectful, and team‑oriented culture EEO Statement Freeman Mathis & Gary, LLP (FMG) is committed to providing equal employment opportunities to all applicants and employees by maintaining a workplace free of discrimination based on race, color, religion, sex, national origin, age, disability, genetic information, or any other protected status as provided by law. FMG complies with all applicable federal, state, and local laws. This position is subject to our drug‑free workplace policy, which includes the ability to pass a pre‑employment drug screen. Employees may be subject to reasonable‑suspicion drug testing in accordance with Firm policies outlined in the Employee Handbook. #J-18808-Ljbffr Freeman Mathis & Gary