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CoorB

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AI Engineer

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Description

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 RAG 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.


Requirements

Mandatory Requirements

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.


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