Azure AI Foundry Architect

Bounteous•Scottsdale, AZ

1d•Remote

About The Position

Bounteous is a global AI Services firm where agentic engineering and human experience converge to deliver transformative business outcomes for the enterprise. We help organizations design, build, and scale AI-driven products, platforms, and processes. With more than 5,000 team members worldwide, Bounteous delivers AI that sticks, powering adoption and outcomes that move organizations from experimentation to true transformation. Bounteous is backed by New Mountain Capital, a New York-based growth-oriented investment firm that emphasizes business building. About the Role We are seeking an experienced Azure AI Foundry Architect to support our Retail AI team, in accelerating enterprise AI adoption through the design, governance, and deployment of secure, scalable AI platforms. This role will be responsible for architecting and governing Azure AI Foundry environments, Azure OpenAI services, model access patterns, AI evaluation frameworks, deployment standards, and enterprise AI governance practices. The ideal candidate brings hands-on experience building production-grade Generative AI and agentic AI solutions while ensuring security, compliance, scalability, and operational excellence. The architect will work closely with business stakeholders, AI engineers, cloud platforms, cybersecurity, enterprise architecture, and data teams to establish best practices and scalable AI deployment patterns across the organization.

Requirements

Education: Bachelor's degree in Computer Science, Information Systems, Engineering, or related field.
Experience: 3-5 years of hands-on experience architecting Azure cloud solutions.
Experience designing enterprise AI or Generative AI platforms.
Proven experience deploying production AI solutions in Azure environments.
Experience collaborating with enterprise architecture, security, and cloud engineering teams.
Strong architecture and systems thinking.
Excellent stakeholder management skills.
Ability to translate business requirements into technology solutions.
Strong consulting and advisory capabilities.
Exceptional documentation and communication skills.
Ability to influence cross-functional teams and executive stakeholders.

Nice To Haves

Advanced degree preferred but not required.
Experience leading AI platform architecture initiatives within large enterprises.
Experience implementing Retail AI use cases.
Experience with Microsoft Fabric, Dataverse, and Power Platform integration.
Exposure to MLOps and LLMOps practices.
Knowledge of Responsible AI and regulatory compliance requirements.
Microsoft Azure AI Engineer Associate or Azure Solutions Architect certifications preferred.

Responsibilities

Azure AI Foundry Architecture & Strategy: Design and implement enterprise-scale Azure AI Foundry architectures.
Define AI platform standards, reusable architectures, and deployment frameworks.
Establish Azure AI Foundry project structures, resource organizations, and environment strategies.
Develop reference architectures supporting enterprise AI initiatives.
Guide adoption of Azure-native AI services across the organization.
Azure OpenAI & Model Architecture: Architect secure and scalable Azure OpenAI implementations.
Define model consumption and deployment strategies.
Design enterprise model access patterns supporting internal business applications.
Evaluate model selection strategies for various business use cases.
Optimize AI platform performance, reliability, scalability, and cost management.
Support LLM deployment lifecycle management.
AI Foundry Resource & Project Management
Information Security Responsibilities: Promote and enforce awareness of key information security practices, including acceptable use of information assets, malware protection, and password security protocols.
Identify, assess, and report security risks, focusing on how these risks impact the confidentiality, integrity, and availability of information assets.
Understand and evaluate how data is stored, processed, or transmitted, ensuring compliance with data privacy and protection standards (GDPR, CCPA, etc.).
Ensure data protection measures are integrated throughout the information lifecycle to safeguard sensitive information.