AI Engineer

Experience: 3–7 Years Department: AI / LLM Product Engineering Location: Amman, Jordan Reporting To: Head of AI Employment Type: Full-time Work Type: On-site About The Role We are looking for an experienced AI Engineer to design, build, deploy, and scale AI-powered product capabilities. The ideal candidate has hands-on experience with modern AI/LLM systems, agentic workflows, Retrieval-Augmented Generation (RAG), and AI-assisted software development. You will work closely with our Engineering, Product, Data, and AI teams to turn AI concepts and prototypes into reliable, scalable, and production-ready solutions. Key Responsibilities AI Systems Integration: Build and integrate AI/LLM capabilities using cloud platforms and services such as AWS Bedrock and Azure OpenAI. Agentic Workflows & Orchestration: Design and implement agentic and LLM-driven features using LangGraph, LangChain, or equivalent frameworks. RAG & Retrieval Pipelines: Develop RAG pipelines, vector embeddings, retrieval and grounding mechanisms, prompt engineering, and tool/function-calling workflows. Production Engineering: Transform AI prototypes and experimental concepts into scalable, secure, maintainable, and well-tested production systems. AI-Assisted Development: Leverage modern development tools such as GitHub Copilot, Claude Code, Cursor, or equivalent tools while ensuring generated code meets quality, security, and performance standards. Cross-Functional Collaboration: Partner with Product Managers, Data Engineers, Software Engineers, and AI Researchers to solve complex technical challenges. Quality & Evaluation: Evaluate and improve AI models and workflows using relevant quality, reliability, latency, and performance metrics. Qualifications & Requirements Experience: 3–7 years of professional experience in AI Engineering, Machine Learning Engineering, or Software Engineering with strong hands-on AI/ML experience. AI/LLM Expertise: Practical experience developing AI/LLM-powered applications, intelligent features, prompt engineering, tool/function calling, and LLM orchestration. AI Frameworks: Hands-on experience with LangGraph, LangChain, or comparable AI orchestration frameworks. Programming: Strong Python skills with solid software engineering fundamentals, including OOP, design patterns, and clean code practices. Production Engineering: Experience working with REST/gRPC APIs, data processing, debugging, unit and integration testing, CI/CD, and Git. Problem Solving: Strong analytical and problem-solving skills, with the ability to work independently and effectively within distributed, cross-functional teams. Good to Have Hands-on experience with AWS or Azure.Experience with vector databases such as Milvus, Pinecone, or Qdrant.Knowledge of knowledge graphs and retrieval systems.Exposure to multimodal AI.Experience with Docker, Kubernetes, and modern CI/CD practices.Experience with AI evaluation and observability frameworks such as LangSmith or Phoenix.Familiarity with LLM monitoring and production AI observability.Open-source contributions, technical publications, or a strong portfolio of AI projects. I can also make this more LinkedIn-friendly and shorter, with a stronger opening and candidate-focused language to improve applications.