AI Architecture Senior Manager

Accenture Middle East; Saudi Arabia; On-site; SAR 450,000 - 750,000; 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, including Generative AI and LLMs. You will shape target-state architecture and establish scalable, governed AI foundations.

You will drive technology decisions, enable enterprise-wide adoption, and mentor architecture and data teams while partnering with business stakeholders to ensure responsible AI, security, and governance across programs.

Qualifications

• 12+ years in AI/Enterprise Architecture or related technology leadership roles.
• Experience designing enterprise-scale AI/ML platforms and advanced AI solutions.
• Deep understanding of Generative AI, LLMs, multi-modal models, and AI ecosystem technologies.
• Strong cloud platform experience with Azure, AWS or Google Cloud and AI services.
• Expertise in MLOps, platform engineering, deployment and governance.

Responsibilities

• Define and evolve enterprise AI architecture strategies, frameworks and reference architectures including Generative AI/LLMs and multi-modal solutions.
• Develop and execute AI transformation roadmaps establishing enterprise AI foundations and scalability.
• Lead the integration of AI/ML technologies across data platforms, model ecosystems, MLOps, and cloud infrastructure.
• Architect and build platform components addressing complex business and technical requirements, ensuring security and governance.

Skills

AI architecture

Enterprise architecture

Data platforms

Cloud architecture

MLOps

Model deployment

Governance

Responsible AI

Leadership

Stakeholder influence

Tools

Azure

AWS

Google Cloud

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

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.