Lead AI/ML Engineer

The Lead AI Engineer – Generative AI is responsible for leading the design, development, and delivery of enterprise-grade Generative AI solutions leveraging Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), Agentic AI, and Intelligent Document Processing. The role provides technical leadership across the full AI solution lifecycle, including architecture, engineering standards, team mentoring, client engagement, and deployment of secure and scalable AI solutions. The role will also work closely with government and enterprise clients to deliver compliant AI solutions across Azure and on-premises environments.

Responsibilities:

• Lead the design and implementation of enterprise-grade AI solutions aligned with business objectives and architecture standards
• Define technical architecture, reusable AI frameworks, coding standards, and engineering best practices
• Lead and mentor a mixed onshore/offshore team of AI engineers, conducting design reviews, code reviews, and architecture discussions
• Act as the primary technical point of contact for government and enterprise clients, leading technical workshops, solution walkthroughs, and architecture presentations
• Identify technical risks, define mitigation strategies, and contribute to effort estimation, sprint planning, and milestone reviews
• Evaluate emerging AI technologies, frameworks, and architecture patterns and recommend suitable solutions
• Design and develop production-grade Generative AI applications using LLMs, prompt engineering, function calling, structured outputs, and Responsible AI guardrails
• Define and implement enterprise-scale RAG solutions covering document ingestion, chunking, embeddings, vector indexing, semantic re-ranking, and response evaluation
• Design and implement Agentic AI and multi-agent solutions supporting autonomous reasoning, tool invocation, and dynamic orchestration
• Define agent communication, memory management, state persistence, approval workflows, and human-in-the-loop governance mechanisms
• Lead AI-powered Intelligent Document Processing solutions using OCR, Vision AI, and Azure Document Intelligence
• Design and implement integrations between AI solutions and enterprise platforms including Dynamics 365, SharePoint, ERP/CRM systems, databases, and messaging platforms
• Ensure AI solutions support bilingual Arabic and English interactions, including language detection, intent classification, and context-aware response generation
• Lead deployment of AI workloads on Azure using Azure AI Foundry, Container Apps, Azure Functions, App Service, and API Management
• Establish CI/CD, monitoring, logging, observability, and production deployment standards for AI solutions
• Ensure AI platform performance, scalability, and cost optimization across development and production environments
• Ensure compliance with data residency, security, Responsible AI, audit logging, and AI lifecycle governance requirements

Requirements

• Bachelor’s degree in Computer Science, Engineering, Artificial Intelligence, or a related field
• 5–7+ years of experience, including at least 2–4 years of experience in Generative AI and technical leadership of enterprise AI initiatives
• Strong hands-on experience with Python, FastAPI/Flask, REST APIs, and microservices
• Strong experience with Generative AI, Azure OpenAI, GPT models, prompt engineering, function calling, structured outputs, and Responsible AI
• Hands-on experience designing and implementing RAG solutions using Azure AI Search, vector databases, embeddings, re-ranking, and evaluation frameworks
• Strong experience with Agentic AI and multi-agent systems using technologies such as Azure AI Foundry Agent Service, Semantic Kernel, LangChain/LangGraph, or MCP
• Experience with Intelligent Document Processing, OCR, Vision AI, and Azure Document Intelligence
• Strong understanding of Azure AI Foundry and Azure services including Container Apps, Azure Functions, App Service, API Management, and Azure Storage
• Experience with enterprise integration, API design, scalability, and performance optimization
• Experience with Cosmos DB, MongoDB, Azure Service Bus, and Redis
• Good understanding of Azure security services including Key Vault, Microsoft Entra ID, RBAC, and audit logging
• Experience with Docker, Git, Azure DevOps, CI/CD, monitoring, and Application Insights
• Strong understanding of Arabic/English bilingual AI and multilingual NLP capabilities
• Strong technical …