AI Architect

We are seeking a hands-on

AI Architect

with extensive experience in

Generative AI, Machine Learning, and Solution Architecture

to design, build, and deliver enterprise-grade AI solutions. The ideal candidate will lead multiple AI initiatives from concept to production, work closely with business stakeholders, and remain actively involved in implementation. This role requires expertise in LLMs, RAG architectures, Azure AI services, AI governance, evaluation frameworks, and scalable cloud-based deployments.

Key Responsibilities:

• Lead the end-to-end design, development, and deployment of AI and GenAI solutions.
• Architect scalable, secure, and high-performance AI systems using Azure AI services.
• Collaborate with business and client stakeholders to translate requirements into AI solutions.
• Build and optimize LLM-powered applications, RAG pipelines, APIs, and AI workflows.
• Design AI solutions for document intelligence, summarization, classification, Q\&A, and automation.
• Implement AI evaluation, observability, guardrails, and responsible AI practices.
• Optimize production AI systems for performance, latency, cost, and accuracy.
• Deploy AI applications using CI/CD, monitoring, logging, and cloud infrastructure.
• Develop traditional ML models where required and mentor junior engineers while ensuring solution quality.

Qualifications:

• 8+ years

of experience in AI/ML engineering and solution architecture.

• 3+ years

of hands-on experience building production-grade GenAI and LLM applications.

• Strong expertise in

Python

,

FastAPI

, Azure AI services, RAG, embeddings, vector databases, and LLM orchestration frameworks.

• Experience with AI agents (LangGraph, AutoGen, Semantic Kernel, CrewAI), AI evaluation (RAGAS, BLEU, Precision, Recall, F1), and observability tools (LangSmith, Langfuse, Azure AI Foundry).
• Solid understanding of NLP, prompt engineering, responsible AI, guardrails, model evaluation, and AI governance.
• Experience deploying AI solutions on Azure with CI/CD, monitoring, and hybrid cloud/on-premise architectures.
• Experience with HuggingFace, open-source LLMs, and enterprise AI deployments.
• Bachelor's degree in Computer Science, AI, Data Science, or a related field (Master's preferred).

Preferred:

• Experience with open-source LLMs (LLaMA, Mistral, Qwen, DeepSeek).
• Exposure to AWS Bedrock or GCP Vertex AI.
• NVIDIA AI Enterprise (Triton, NIM).
• Experience with multilingual NLP (especially Arabic).
• Microsoft Azure certifications (AI-102, DP-100, AZ-305).