Senior Manager - AI Solution Architect, Tech Consulting

About the role

EY is looking for an experienced Senior Manager - AI Solution Architect to join its growing MENA Technology Consulting team in Egypt. You will lead the architecture and delivery of enterprise AI, GenAI and Agentic AI solutions across Egypt and the MENA region.

Key responsibilities

• Lead the architecture of enterprise AI/ML, GenAI and Agentic AI solutions, from design through production deployment.
• Design RAG, vector-data, knowledge graph, semantic layer and unstructured-data architectures.
• Architect scalable training, validation and inference pipelines, feature stores and intelligent document-processing solutions.
• Define and govern MLOps, LLMOps and GenAIOps architectures and practices.
• Establish responsible AI, model monitoring, evaluation, data/model lineage and governance controls.
• Advise senior stakeholders on AI architecture, technology choices, scalability and production readiness.
• Lead solutioning, proposals, RFP responses and business development for AI opportunities.
• Provide architecture leadership and mentoring across multidisciplinary Data & AI teams.

Required profile

• Strong experience in AI/ML solution architecture, data science, ML engineering or GenAI architecture, with demonstrated leadership responsibility.
• Proven experience architecting and delivering enterprise-scale AI/ML and GenAI solutions.
• Strong understanding of the end-to-end AI lifecycle, from data and feature engineering through model deployment, monitoring and operations.
• Strong client-facing, C-suite communication and stakeholder-management capabilities.
• Industry experience, preferably in financial services, government and public sector, energy and utilities, telecom, consumer and retail, or real estate and infrastructure.
• Prior Big Four, consulting, system integration or technology consulting experience is highly preferred.
• Experience across Egypt/MENA and readiness to travel across the MENA region based on client needs.

Required skills

• AI platforms: Azure AI/OpenAI, AWS Bedrock/SageMaker, Google Vertex AI, Databricks Mosaic AI, IBM watsonx, Hugging Face.
• GenAI and agentic AI: LLMs/SLMs, RAG and graph RAG, AI agents, multi-agent systems, knowledge graphs, vector databases, orchestration frameworks.
• Advanced AI: computer vision, multimodal AI, OCR/document AI, conversational AI, predictive AI, optimization and real-time decisioning.
• AI engineering: PyTorch, TensorFlow, feature stores, training/inference pipelines, APIs and enterprise integration.
• AI operations: MLOps, LLMOps and GenAIOps, model serving, evaluation, observability, monitoring and data/model lineage.
• Infrastructure: cloud, hybrid and on-premise AI architectures, Kubernetes, Docker and GPU-enabled AI infrastructure.
• Responsible AI: governance, explainability, fairness and bias controls, privacy, safety guardrails, human oversight, model risk and auditability.