Design, build, fine-tune, evaluate, and deploy production-grade LLM solutions for digital banking. Responsibilities include RAG pipelines, knowledge graphs, agentic AI workflows, LLM evaluation, LLMOps/MLOps, model monitoring, CI/CD, security, privacy, and responsible AI. The role collaborates with architects, developers, and banking clients to deliver compliant AI solutions across the GCC.
This is a remote position.
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.
- 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.
Similar Jobs
Big Data • Information Technology • Productivity • Software • Analytics • Business Intelligence • Consulting
Leads strategic customer engagements by discovering operational challenges, architecting and prototyping secure AI and LLM solutions, executing proof-of-value projects, and demonstrating measurable business impact to executives. The role combines presales, value engineering, enterprise AI architecture, agentic systems, optimization, production ML/LLMOps, data engineering, security, and executive presentations. It also develops reusable methodologies, supports adoption and value realization, and mentors junior team members.
Top Skills:
Aws BedrockAzure AiCelonis PlatformGcp Vertex AiHugging FaceLlmsProcess Intelligence PlatformPythonPyTorchRagScikit-LearnSQLTensorFlowXgboost
Artificial Intelligence • Information Technology • Software
Lead enterprise AI and machine learning architecture, delivery, and consulting engagements across the UAE. Build production-grade ML, deep learning, RAG, LLM agent, and MLOps systems on AWS and Azure. Advise senior client stakeholders, mentor AI and quantitative teams, resolve technical and organizational friction, and establish secure, compliant AI platforms using modern cloud, deployment, and governance practices.
Top Skills:
AWSAws SagemakerAzureAzure OpenaiCi/CdDockerHugging FaceKubernetesLangchainLlamaindexLlm AgentsLoraMlopsOllamaPii MaskingPyTorchQloraRetrieval-Augmented Generation (Rag)TensorFlowTgiVector DatabasesVllmZero-Trust Security
Software
Build and deploy production AI systems, including agents, RAG pipelines, evaluation infrastructure, model routing, and data connectors. Embed with real estate investment clients to scope, prototype, deploy, and productionize AI solutions. Partner with go-to-market teams, explain technical trade-offs, maintain client relationships, and convert custom implementations into reusable platform capabilities.
Top Skills:
AWSExcelGoogle Cloud PlatformLanggraphLarge Language ModelsLlamaindexMcpAzurePythonRagTypescript
What you need to know about the Dublin Tech Scene
From Bono and Oscar Wilde to today's tech leaders, Dublin has always attracted trailblazers, with more than 70,000 people working in the city's expanding digital sector. Continuing its legacy of drawing pioneers, the city is advancing rapidly. Ireland is now ranked as one of the top tech clusters in the region and the number one destination for digital companies, with the highest hiring intention of any region across all sectors.
