AI LLM Technology Architecture Associate Director

Accenture Middle East; Saudi Arabia; On-site; SAR 300,000 - 520,000; Full time

Job summary

Accenture Middle East seeks a senior AI Architect to lead the enterprise AI strategy, aligning business goals with a coherent technical vision. You will own end-to-end AI platform architecture, including memory, context management, and knowledge graphs, across multiple domains.

Expect collaboration with senior leaders to drive investments and practical roadmaps. The role requires extensive experience in deploying enterprise-grade AI/ML solutions, including LLM and generative AI, with a focus on

Qualifications

• Proven experience in designing & deploying enterprise AI solutions using agentic, generative and classical AI/ML on at least one cloud vendor.
• Experience architecting and operationalizing LLM driven application architectures.
• Strong background in security, governance, observability and scalability across domains.

Responsibilities

• Partner with CIOs/CTOs and business leaders to shape enterprise AI strategy and translate goals into a technical vision.
• Lead enterprise AI assessments and build implementation roadmaps sequencing investments for competitive advantage.
• Own end-to-end technical solution for complex AI platforms ensuring cohesive domain design and standards.
• Define memory, context, and knowledge graph strategies; drive multi-agent ecosystems with governance.
• Establish architecture standards, MCP control plane, and risk scoring across internal and third-party systems.
• Produce authoritative architecture artifacts and act as a thought leader in AI externally.

Skills

Enterprise AI architecture

LLM & Generative AI

NLP solutions

Machine Learning & Deep Learning

Scalable data platforms

Security governance & observability

FinOps / cost optimization

Tools

Cloud platforms

Vector search / knowledge graphs

AI gateway / registries

Job description

THE WORK

Partner with CIOs CTOs and business leaders to shape the enterprise AI strategy connecting business goals to a coherent sequenced technical visionLead enterprise AI assessments and build enterprise AI implementation roadmaps that sequence investments for lasting competitive advantageOwn the complete end-to-end technical solution for complex AI platforms ensuring every domain is cohesively designed and aligned to business objectives and enterprise standardsTranslate the governing architecture principles into a concrete defensible technical solution that domain teams build againstBuild innovative prototypes and proofs of concept hands-on using emerging technologies to de-risk decisions and prove value earlyPerform technology assessments and comparisons making definitive evidence-based recommendations on tools frameworks and platformsSet the architectural direction for model- and tool-agnostic multi-agent ecosystems orchestration memory and tool skill use governed through a registry-bound AI GatewayEstablish the agent registry and certification model that mandates no uncertified agent reaches productionDefine memory as a first-class abstracted platform service decoupled from any underlying vendor engineDefine the foundation model and inference strategy adaptation fine-tuning and dynamic cost quality latency-aware routingSet the standards for high-throughput low-latency inferencing and classical ML deployment within unified production-ready platformsOwn the architecture of the enterprise context layer knowledge graphs ontologies vector search and semantic retrieval grounding the solution in client knowledgeSet the design direction for context assembly and memory that manages prompts context windows and conversational state across the platformBe accountable for security governance observability performance and scalability addressed holistically and consistently across every domainEstablish the identity and authorization model per-agent identity IAM IAP binding and defense-in-depth enforcementDefine the layered guardrail framework applied at every boundary balancing protection with performanceGovern the MCP control plane registry gateway and risk scoring across all internal and third-party serversMandate adopt-over-build for productized evaluation and observability stacksEstablish FinOps as a first-class concern usage labelling gateway-enforced budgets and cost-per-archetype as a planning inputMake the definitive decisions on design patterns reference architectures frameworks and technology selections balancing innovation with pragmatismLead and integrate the work of domain architects and specialists resolving cross-domain tensions into a unified enterprise-ready systemBuild the practice s reusable reference architectures frameworks and assets with a deliberate adopt-over-build stanceConduct deep-dive architecture workshops and working sessions with client executives and engineering teamsProduce and govern the authoritative architecture artifacts blueprints reference architectures ADRs and integration specifications that guide delivery at scaleServe as a recognized thought leader in AI shaping the practice s point of view and representing the firm externally through publications and conference engagements Proven experience in designing & deploying enterprise grade advanced ai solutions using agentic, generative and classical AI/ML using at least one cloud vendor. Proven experience in the LLM and Generative AI space. Proven experience architecting and operationalizing LLM driven application architecture patterns. Proven experience in engineering, machine learning, deep learning and NLP solutions and applications. Minimum of 6 years of experience as a machine architect in the industry designing big data, machine learning. large scale analytical engineering solutions