Full-Stack AI Engineer

Job Title: Full-Stack AI Engineer

Location: Amman, Jordan (On-site)

Experience: 1–2+ Years in Production Environments

Role Overview

We are seeking a highly skilled Full-Stack AI Engineer to join our team. You will be responsible

for the end-to-end lifecycle of AI products, from designing sophisticated RAG pipelines and

fine-tuning LLMs to deploying scalable models on bare-metal and cloud infrastructure. The ideal candidate thrives at the intersection of software engineering and cutting-edge AI.

Key Responsibilities

● AI Development: Design, implement, and optimize RAG and CAG systems.

● Model Optimization: Perform fine-tuning and quantization of LLMs to balance performance and resource efficiency.

● Agentic Frameworks: Build autonomous workflows using agentic AI frameworks (e.g., LangGraph, AutoGPT, or CrewAI).

● Production Deployment: Deploy and maintain AI models in production environments, with a focus on high availability and low latency.

● Backend & Infrastructure: Develop robust APIs in Python and manage containerized environments using Docker.

● Database Management: Architect and query diverse data systems including SQL, NoSQL (MongoDB), and Graph databases.

Technical Requirements

● Core Languages: Mastery of Python and a strong command of Linux environments.

● AI/ML Expertise: Hands-on experience with LLM integration, prompt engineering, and vector databases.

● DevOps & Tooling: Proficient in Docker and version control systems (Git).

● Environment Experience: At least 1–2 years of experience deploying models in production, preferably with bare-metal server management.

● Data Systems: Excellent command of SQL; Experience with NoSQL databases (e.g., MongoDB), and Graph databases.

Preferred & Bonus Skills

● Experience with Apache Kafka for real-time data streaming.

● Knowledge of Graph-based RAG architectures.

Soft Skills

● Analytical Thinking: Ability to decompose complex problems into manageable technical tasks.

● Problem-Solving: A proactive mindset for debugging production issues and optimizing model bottlenecks.

● Communication: Fluent in technical English and capable of documenting complex workflows.