Azure AI Technical Architect

We are recruiting for a Senior AI ML Technical Architect to join a leading technology consultancy in Abu Dhabi on a 12-month contract This is an opportunity for an experienced AI Architect to lead the design development and deployment of enterprise-scale Generative AI and Agentic AI solutions The successful candidate will combine strong hands-on technical expertise with architectural leadership designing scalable AI platforms advanced Retrieval-Augmented Generation RAG solutions and intelligent multi-agent systems strong strong strong

strong Architect and deliver enterprise-scale Generative AI and Agentic AI solutions using Large Language Models LLMs and Small Language Models SLMs Design multi-agent orchestration frameworks including context management memory and persistent agent interactions Develop advanced RAG architectures including vector databases embeddings semantic search and hybrid retrieval Build AI applications using Lang Chain Lang Graph Semantic Kernel and Agno Implement Model Context Protocol MCP integrations to connect AI agents with enterprise systems Architect secure APIs and enterprise integrations using REST GraphQL gRPC and event-driven architectures Lead AI model deployment across Azure AWS GCP and on-premises environments Establish best practices for model evaluation performance optimization security and AI governance

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8+ years experience in Software Engineering, Data Engineering or AI systems. 4+ years experience designing enterprise-scale architectures and distributed systems. 2+ years hands-on experience developing Generative AI and LLM-based solutions. Strong cloud platform experience across Microsoft Azure Strong experience with LLMs such as GPT, Claude, LLaMA and open-source models. Proven expertise in Agentic AI, multi-agent systems, RAG architectures and vector databases.

Hands-on experience with Lang Chain, Lang Graph, Semantic Kernel or equivalent agent orchestration frameworks. Strong understanding of LLM fine-tuning, model optimization and inference pipelines. Experience working with Python, PyTorch, Tensor Flow and Hugging Face. Experience with Docker, Kubernetes, CI/CD pipelines and MLOps. Excellent understanding of enterprise integration, API architecture, authentication and security.