AI Engineer

CoorB; Jeddah; Presencial; SAR 420.000 - 680.000; Jornada completa

Descripción de la vacante

CoorB is seeking a Senior AI Engineer to design, build, and deploy AI solutions for digital banking across the GCC. You will develop production-grade LLM applications including retrieval-augmented systems, knowledge graphs, and fine-tuned models that deliver measurable value to banking clients.

Responsibilities include building RAG pipelines, maintaining knowledge graphs, fine-tuning LLMs, developing agentic AI workflows, and implementing LLM evaluation and MLOps practices in regulated

Formación

• 5–7 years in software, ML or AI engineering, with at least 2 years building LLM-based applications.
• Strong Python; hands-on with LangChain, LlamaIndex or similar frameworks.
• Proven experience building RAG systems in production.
• Hands-on with vector databases (Pinecone, Weaviate, Milvus, pgvector, Azure AI Search or similar).
• Experience with knowledge graphs and graph databases.
• Proven experience fine-tuning open-source LLMs (Llama, Mistral, Qwen or similar) using Hugging Face tooling.
• Experience with commercial LLM APIs (OpenAI/Azure OpenAI, Anthropic, Google Gemini).
• Experience building agentic AI and multi-agent solutions, including MCP (Model Context Protocol).
• On premises, Cloud experience on Azure, AWS or GCP, plus Docker and Kubernetes.
• Solid grasp of prompt engineering, embeddings and LLM evaluation methods.
• Arabic NLP or multilingual model experience.
• Experience in banking, fintech or other regulated industries.
• Familiarity with SAMA or GCC regulatory and data-residency requirements.

Responsabilidades

• Design and build b R b AG pipelines document ingestion chunking embeddings hybrid search and re-ranking
• Build and maintain knowledge bases and knowledge graphs for example Neo4j or GraphRAG approaches
• Fine-tune LLMs LoRA QLoRA PEFT on domain-specific data and evaluate them against base models
• Develop agentic AI workflows including tool calling multi-step orchestration and memory
• Set up LLM evaluation frameworks to measure accuracy hallucination rate latency and cost
• Deploy and operate models in production LLMOps MLOps including monitoring versioning and CI CD
• Apply security data privacy and responsible AI practices suited to regulated banking environments
• Work with architects developers and client stakeholders to turn business needs into AI solutions

Conocimientos

Python

LangChain

LlamaIndex

RAG systems

Vector DBs

Knowledge graphs

LLM fine-tuning

Agentic AI

Docker

Kubernetes

Prompt engineering

Arabic NLP

Banking domain

Cloud platforms

Herramientas

Neo4j

GraphRAG

Pinecone

Weaviate

Milvus

pgvector

Azure AI Search

Docker

Kubernetes

Hugging Face

OpenAI API

Azure OpenAI

LangChain integrations

Descripción del empleo

CoorB is looking for a Senior AI Engineer to design build and deploy AI solutions for digital banking You will build production-grade LLM applications including retrieval-augmented systems knowledge graphs and fine-tuned models that deliver measurable business value to our banking clients across the GCC

Key Responsibilities

• Design and build b R b AG pipelines document ingestion chunking embeddings hybrid search and re-ranking
• Build and maintain knowledge bases and knowledge graphs for example Neo4j or GraphRAG approaches
• Fine-tune LLMs LoRA QLoRA PEFT on domain-specific data and evaluate them against base models
• Develop agentic AI workflows including tool calling multi-step orchestration and memory
• Set up LLM evaluation frameworks to measure accuracy hallucination rate latency and cost
• Deploy and operate models in production LLMOps MLOps including monitoring versioning and CI CD
• Apply security data privacy and responsible AI practices suited to regulated banking environments
• Work with architects developers and client stakeholders to turn business needs into AI solutions

All of the following are required:

• 5–7 years in software, ML or AI engineering, with at least 2 years building LLM-based applications.
• Strong Python; hands-on with LangChain, LlamaIndex or similar frameworks.
• Proven experience building RAG systems in production.
• Hands-on with vector databases (Pinecone, Weaviate, Milvus, pgvector, Azure AI Search or similar).
• Experience with knowledge graphs and graph databases.
• Proven experience fine-tuning open-source LLMs (Llama, Mistral, Qwen or similar) using Hugging Face tooling.
• Experience with commercial LLM APIs (OpenAI/Azure OpenAI, Anthropic, Google Gemini).
• Experience building agentic AI and multi-agent solutions, including MCP (Model Context Protocol).
• On premises, Cloud experience on Azure, AWS or GCP, plus Docker and Kubernetes.
• Solid grasp of prompt engineering, embeddings and LLM evaluation methods.
• Arabic NLP or multilingual model experience.
• Experience in banking, fintech or other regulated industries.
• Familiarity with SAMA or other GCC regulatory and data-residency requirements.