Generative AI Engineer

About the role

We are seeking a Generative AI Engineer to join our technology team and design, develop, and deploy AI‑powered solutions using Large Language Models (LLMs), generative AI frameworks, and modern machine learning technologies.

Key responsibilities

• Design and build autonomous AI agents and multi‑agent systems that can reason, plan, collaborate, and execute complex business and technical workflows.
• Integrate and optimise LLMs for enterprise use cases, develop prompt‑engineering techniques, and implement function calling and tool usage.
• Build Retrieval‑Augmented Generation pipelines, manage short‑term and long‑term memory, and optimise embeddings and vector search.
• Connect AI agents with internal systems, databases, and external APIs, enabling agents to perform business actions and integrate with automation workflows.
• Develop agent workflows using frameworks such as LangGraph, Semantic Kernel, and Microsoft Agent Framework, ensuring modular and reusable components.
• Create production‑grade AI services in Python, design scalable APIs and microservices, and apply testing, version control, and containerisation best practices.
• Evaluate agent performance, implement observability, logging, tracing, and apply guardrails to reduce hallucinations.
• Deploy and operate AI solutions on cloud platforms, ensuring security, privacy, responsible AI, and cost‑effective infrastructure.

Required profile

• 1+ years of experience building, optimising, and deploying production‑ready applications powered by LLMs.
• Bachelor's degree in Computer Science or related field.
• Advanced proficiency in English; Arabic preferred.
• Strong analytical, problem‑solving, and teamwork skills.

Required skills

• Python programming
• Large Language Models (LLMs) and prompt engineering
• Retrieval‑Augmented Generation (RAG), embeddings, vector databases
• API development and system integration
• LangGraph, Semantic Kernel, Microsoft Agent Framework
• Microservices, asynchronous processing, containerisation
• Version control (Git), testing, CI/CD pipelines
• Cloud platforms (AWS, Azure, GCP) and security best practices