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
12+ years of 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.
