AI Architecture Senior Manager

Accenture Middle East; Riyadh; On-site; SAR 350,000 - 550,000; Full time

Job summary

Accenture Middle East is seeking an AI Architecture Senior Manager to lead strategy, design, and implementation of enterprise-scale AI platforms and architectures. You will drive target-state AI architecture, governance, and secure foundations to accelerate enterprise-wide AI adoption.

You will oversee AI/ML platform development, integration across data ecosystems, MLOps, and security, while mentoring architecture and engineering teams in a fast-paced environment.

Qualifications

• Proven experience in AI Architecture and Enterprise Architecture leadership.
• Deep understanding of Generative AI, LLMs, and multi-modal models.
• Strong cloud experience with AI/ML services (Azure, AWS, Google Cloud).
• Experience with MLOps, AI governance, and security controls.

Responsibilities

• Define and evolve enterprise AI architecture strategies and reference architectures.
• Assess emerging AI technologies and lead platform adoption.
• Develop AI transformation roadmaps for scalable, enterprise foundations.
• Design end-to-end AI platforms for model development, deployment, monitoring, and governance.
• Lead integration of AI/ML across data platforms, MLOps, and cloud infrastructure.
• Establish AI operational standards including observability and resilience.
• Implement Responsible AI, security, privacy, risk management, and compliance controls.
• Provide leadership and mentorship to architecture, engineering, and data teams.

Job description

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.