Senior AI Engineer – FinTech Software House – Dubai Based - AED 25k PCM

Senior AI Engineer – FinTech Software House – Dubai Based Global leading FinTech software house seeks an experienced Senior AI Engineer to join their Global HQ in JLT, Dubai (UAE), leading the tactical execution of the company’s AI strategy. It is essential that you are already based in Dubai as they will not pay for relocation. Reporting directly into their Chief Technology Officer (CTO), you’ll join a truly global business with offices and clients based across North America, Europe and Asia, providing trading software across trading, logistics and risk management. You’ll work closely with some of the most experienced software designers, developers and business analysts in the industry, providing the trading community with the most robust, user-friendly, enterprise wide software package. You’ll join a truly world class trading software business, who continue to launch new products that evolve with the changing global technological and trading landscapes, and who have made AI the cornerstone of their business. The company is executing an AI strategy which will add new capabilities and transform the operating model in addition to delivering benefits that enhance existing and emerging AI related products and services to Customers. Role purpose: 100% focused on the tactical execution of the company’s AI strategy specifically in the design and implementation of AI/ML use cases built on Large Language Models (LLMs/RAG) and Natural Language Processing (NLP), Machine Learning (ML), Generative AI (GenAI), Robotic Process Automation (RPA) and Decision Making (AgenticAI). • The role will deliver a broad range of prioritized use cases for internal optimization and external product benefit, therefore candidates will need skills and experience across the key AI/ML types with an estimated split of skills as follows:60% AI skills focused on AI/ML models [LLMs/NLP/ML] • 30% AI skills to automate, assist & augment [GenAI, RPA, AgenticAI] • 10% AI skills for developing & operationalizing AI/ML). This is a hands-on role for someone who can move smoothly between experimentation and production, and who has demonstrable experience in converting emerging AI/ML capabilities into measurable business outcomes. • Technical Roles and Responsibilities:Lead the design and implementation of AI-powered conversational experiences for an existing SaaS platform. • Define the roadmap for transforming legacy workflows into chat-based, assistant-driven, and agentic user journeys. • Build and optimize LLM applications using prompting, RAG, tool use, workflow orchestration, and multi-step reasoning patterns. • Develop evaluation frameworks for quality, latency, accuracy, hallucination risk, safety, and business impact. • Architect scalable AI services for enterprise environments, including observability, failover, auditability, and access controls. • Design retrieval pipelines using structured and unstructured enterprise data sources. • Establish guardrails for compliance, privacy, security, and responsible AI deployment. • Partner with product, design, data, security, and go-to-market teams to define use cases and deliver production features. • Implement internal use cases that enhance productivity tool content generation, product code generation, product code testing, CI/CD and engineering process efficiencies. • Stay current on advances in LLMs, agent frameworks, vector search, model serving, and AI infrastructure. Technical Experience and Expertise: • A broad range of technology knowledge to an appropriate level of competency/qualification including but not limited to:Languages: Python, SQL, ideally TypeScript or Go • LLM/AI: OpenAI APIs, Anthropic, open-source LLMs, embeddings, fine-tuning, evaluation • Frameworks: LangChain, LlamaIndex, DSPy, FastAPI, MLflow, Hugging Face • Data & Retrieval: Vector databases, Elasticsearch/OpenSearch, metadata filtering, reranking • Infra: Azure, AKS, Docker, Redis, Postgres, SQL • Engineering: GraphQL service integration, distributed systems, observability, testing, CI/CD • Responsible AI: Guardrails, red teaming, privacy, model risk management Salary: Flexible but ideally AED 20-25k PCM + package • Experience sought:5+ years of software engineering, machine learning engineering, and/or applied AI experience. • Masters in Computer Science, Machine Learning, Artificial Intelligence or a related field. • 2+ years of hands-on experience building LLM or generative AI systems in production. For more information, please e-mail an up-to-date copy of your CV to Ben at [email protected] Show more Show less

Experience sought: 5+ years of software engineering, machine learning engineering, and/or applied AI experience. Masters in Computer Science, Machine Learning, Artificial Intelligence or a related field. 2+ years of hands-on experience building LLM or generative AI systems in production.

Lead the design and implementation of AI-powered conversational experiences for an existing SaaS platform. Define the roadmap for transforming legacy workflows into chat-based, assistant-driven, and agentic user journeys. Build and optimize LLM applications using prompting, RAG, tool use, workflow orchestration, and multi-step reasoning patterns. Develop evaluation frameworks for quality, latency, accuracy, hallucination risk, safety, and business impact. Architect scalable AI services for enterprise environments, including observability, failover, auditability, and access controls. Design retrieval pipelines using structured and unstructured enterprise data sources. Establish guardrails for compliance, privacy, security, and responsible AI deployment. Partner with product, design, data, security, and go-to-market teams to define use cases and deliver production features. Implement internal use cases that enhance productivity tool content generation, product code generation, product code testing, CI/CD and engineering process efficiencies. Stay current on advances in LLMs, agent frameworks, vector search, model serving, and AI infrastructure.