AI LLM Technology Architecture Associate Director📣 Job Ad

About the Role

Accenture Middle East is seeking an AI LLM Technology Architecture Associate Director to join their team in Riyadh, Riyadh. This full-time role requires over 10 years of experience and involves serving as a definitive technical authority on AI architecture within client engagements and across the practice. The Associate Director will own the complete, end-to-end architecture of advanced AI platforms and solutions, ensuring cohesive design, technical soundness, and alignment with client business objectives and enterprise-grade standards.

Key Responsibilities and Strategic Impact

This position operates at an executive level, collaborating with CIOs, CTOs, and senior business leaders to shape enterprise AI strategy. The role involves connecting business goals and transformation agendas to a coherent technical vision, ensuring AI investments deliver lasting competitive advantage. The Associate Director will also lead and integrate the work of multiple domain architects and subject matter specialists, providing architectural vision, technical governance, and cross-domain coherence for unified, enterprise-ready systems.

Core Architectural Duties

• Partner with CIOs, CTOs, and business leaders to shape enterprise AI strategy, connecting business goals to a coherent, sequenced technical vision.
• Lead enterprise AI assessments and build implementation roadmaps that sequence investments for competitive advantage.
• Own the complete, end-to-end technical solution for complex AI platforms, ensuring cohesive design and alignment to business objectives and enterprise standards.
• Translate governing architecture principles into concrete, defensible technical solutions for domain teams.
• Build innovative prototypes and proofs of concept hands-on, using emerging technologies to de-risk decisions and prove value.
• Perform technology assessments and comparisons, making definitive, evidence-based recommendations on tools, frameworks, and platforms.
• Set the architectural direction for model- and tool-agnostic multi-agent ecosystems, including orchestration, memory, and tool/skill use, governed through a registry-bound AI Gateway.
• Establish the agent registry and certification model to ensure only certified agents reach production.
• Define memory as a first-class abstracted platform service, decoupled from underlying vendor engines.
• Define the foundation model and inference strategy, including adaptation, fine-tuning, and dynamic cost/quality/latency-aware routing.
• Set standards for high-throughput, low-latency inferencing and classical ML deployment within unified, production-ready platforms.
• Own the architecture of the enterprise context layer, including knowledge graphs, ontologies, vector search, and semantic retrieval, grounding solutions in client knowledge.
• Set the design direction for context assembly and memory that manages prompts, context windows, and conversational state across the platform.
• Be accountable for security, governance, observability, performance, and scalability addressed holistically and consistently across every domain.
• Establish the identity and authorization model, including per-agent identity, IAM/IAP binding, and defense-in-depth enforcement.
• Define the layered guardrail framework applied at every boundary, balancing protection with performance.
• Govern the MCP control plane, including registry, gateway, and risk scoring, across all internal and third-party servers.
• Mandate adopt-over-build for productized evaluation and observability stacks.
• Establish FinOps as a first-class concern, including usage labelling, gateway-enforced budgets, and cost-per-archetype as a planning input.
• Make definitive decisions on design patterns, reference architectures, frameworks, and technology selections, balancing innovation with pragmatism.
• Lead and integrate the work of domain architects and specialists, resolving cross-domain tensions into a unified, enterprise-ready system.
• Build the practice’s reusable reference architectures, frameworks, and assets, with an adopt-over-build stance.
• Conduct deep-dive architecture workshops and working sessions with client executives and engineering teams.
• Produce and govern authoritative architecture artifacts, including blueprints, reference architectures, ADRs, and integration specifications, to guide delivery at scale.
• Serve as a recognized thought leader in AI, shaping the practice’s point of view and representing the firm externally through publications and conference engagements.

Qualifications and Experience

• A minimum of 10 years of experience in AI architecture or a related field.
• Demonstrated expertise in classical machine learning, generative AI, and agentic systems.
• Ability to operate at an executive level, engaging with senior business and technology leaders.
• Proven track record of leading complex AI platform architectures from end-to-end.
• Strong understanding of non-functional requirements across security, observability, governance, performance, and scalability in AI solutions.

Work Environment

This is a full-time position based in Riyadh, Riyadh, within Accenture Middle East. The role involves working with cross-functional engineering teams, domain architects, and client stakeholders, requiring strong leadership and communication skills to ensure clarity and confidence in execution.

Application Process

Candidates interested in this opportunity are encouraged to apply. Salary details will be discussed during the interview process.