Job Opportunity: Full-Stack AI Engineer at Altibbi

An exciting job opportunity is available at Altibbi for a highly skilled Full-Stack AI Engineer with a passion for cutting-edge technologies and scalable AI systems. The role involves full ownership of the AI product lifecycle-from designing advanced RAG pipelines and fine-tuning large language models (LLMs) to deploying solutions across bare-metal and cloud infrastructure.

Ideal for experienced professionals in AI development and software engineering, this role sits at the intersection of intelligent system design and real-world application. A strong foundation in both backend architecture and modern AI workflows is essential for success.

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.

We refresh listings regularly, but some roles close early on the source platform.