Job Description

Roles & Responsibilities

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.

Desired Candidate Profile

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.

Full-Stack AI Engineer Altibbi