AI Architecture Senior Manager

Role Overview As an AI Architecture Senior Manager, you will lead the strategy, design, and implementation of enterprise-scale AI platforms and architectures, enabling the adoption of advanced AI technologies including Generative AI, Large Language Models (LLMs), and multi-modal models. You will define the target-state AI architecture, drive technology decisions, and establish scalable, secure, and governed AI foundations that accelerate business innovation and enterprise-wide AI adoption. Key Responsibilities - Define and evolve enterprise AI architecture strategies, frameworks, and reference architectures, including Generative AI, LLMs, and multi-modal AI solutions. - Assess emerging AI technologies, platforms, and architectural patterns, providing leadership on technology selection and adoption. - Develop and execute AI transformation roadmaps that establish enterprise AI foundations and long-term scalability. - Design and operationalize end-to-end AI platforms supporting model development, deployment, monitoring, governance, and lifecycle management. - Lead the integration of AI/ML technologies across data platforms, model ecosystems, MLOps, cloud infrastructure, security, and governance frameworks. - Architect and build custom AI platform components to address complex business and technical requirements. - Optimize compute infrastructure, model-serving environments, and distributed AI workloads for scalability, performance, reliability, and cost efficiency. - Establish enterprise AI operational standards, including observability, monitoring, performance management, and platform resilience. - Implement Responsible AI, security, privacy, risk management, and compliance controls across AI solutions and platforms. - Partner with business and technology stakeholders to define AI governance models, architecture standards, and best practices. - Provide technical leadership and mentorship to architecture, engineering, and data teams throughout AI initiatives. Job Qualifications Basic Qualifications - Proven experience in AI Architecture, Enterprise Architecture, Data Platforms, Cloud Architecture, or related technology leadership roles. - Proven experience designing and implementing enterprise-scale AI/ML platforms and advanced AI solutions. - Deep understanding of Generative AI, Large Language Models (LLMs), multi-modal models, and AI ecosystem technologies. - Strong experience with cloud platforms such as Azure, AWS, or Google Cloud and their AI/ML services. - Expertise in MLOps, AI platform engineering, model deployment, monitoring, and operationalization. - Experience implementing AI security, governance, compliance, and Responsible AI frameworks. - Strong architecture leadership experience with the ability to influence senior stakeholders and technology strategy. Preferred Qualifications - Experience establishing Enterprise AI Foundations, AI Centers of Excellence (CoE), or AI Transformation programs. - Knowledge of vector databases, Retrieval-Augmented Generation (RAG), AI agents, orchestration frameworks, and advanced AI architecture patterns. - Experience with Kubernetes, containerization, distributed computing, and high-performance AI infrastructure. - Expertise in AI observability, model performance optimization, platform reliability, and cost management. - Strong consulting, stakeholder management, and executive communication skills. - Relevant certifications in Cloud Architecture, Artificial Intelligence, Machine Learning, or Enterprise Architecture are preferred.

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