Architect, Enterprise AI

Overview Due to growth, we are adding a Architect, Enterprise AI to our team! The Architect, Enterprise AI is responsible for designing, governing, and advancing the enterprise architecture strategy for Artificial Intelligence and Agentic AI capabilities across the organization. This role partners with Enterprise Architecture, Platform Engineering, Data Engineering, and Product teams to define scalable AI architecture patterns, reference architectures, and governance frameworks that enable responsible and secure use of AI technologies. The Architect serves as the enterprise subject matter expert on AI platforms, generative AI, and agentic workflows, ensuring alignment with enterprise architecture principles, security requirements, and regulatory standards while enabling innovation and business value. Is this you? Find out more below! Responsibilities How do I make an impact on my team? - Define and maintain the enterprise AI architecture strategy, including standards and reference architectures that support scalable adoption of AI, generative AI, and agentic AI capabilities across the organization. - Establish and maintain enterprise AI architecture patterns, including design standards for generative AI, agentic workflows, retrieval-augmented generation (RAG), model orchestration, and enterprise AI service integration. - Develop and implement AI governance frameworks and architectural guardrails to ensure responsible, secure, and compliant use of AI technologies across the enterprise. - Define AI platform strategy by evaluating and recommending AI platforms, large language model providers, orchestration frameworks, and supporting tooling aligned with enterprise architecture standards. - Establish AI integration patterns that enable AI capabilities to integrate with enterprise platforms, APIs, data platforms, and cloud services while maintaining scalability and reliability. - Define and promote Agentic AI architectural patterns, including standards for workflow orchestration, tool integration, memory/context management, and human-in-the-loop capabilities. - Ensure adherence to Responsible AI and regulatory compliance requirements, including standards for data privacy, auditability, model transparency, and ethical AI practices. - Define architectural standards for AI operations (LLMOps/MLOps) including model lifecycle management, monitoring, observability, deployment pipelines, and operational controls. - Establish AI security and cost management practices, including secure model access, data protection standards, usage controls, and architectural patterns that optimize AI infrastructure and consumption costs. - Other duties as assigned. Qualifications What our team expects ** from you?** Bachelor's degree in Computer Science, Information Systems, Software Engineering, or a related field, or equivalent work experience, required. Certification/Licenses: - AWS Certified Solutions Architect Professional and AWS Certified Machine Learning -- Specialty certification preferred. - Responsible AI / AI Governance certification preferred. - Industry-recognized Certified AI Professional certification or equivalent AI/ML certification preferred. 10+ years of experience in software development or architecture, including a minimum of 5 years focused on Artificial Intelligence and Machine Learning technologies,