Conversational AI Engineer

Job Description Roles & Responsibilities I am working with a client who are a specialist AI and data consultancy dedicated to transforming the regional corporate landscape through bespoke, high-impact intelligent systems. Based in the UAE, we partner with organizations across diverse sectors-with a deep-rooted expertise in Financial Services and Banking-to bridge the gap between complex data and actionable business strategy. The Artificial Intelligence (AI) Engineer is a specialist role focused on the engineering, deployment, and scaling of advanced AI systems to drive the Bank s digital and operational transformation. This position is responsible for building the robust technical foundations required for enterprise-grade applications, including Conversational AI agents, operations automation, and Generative AI initiatives. By developing high-performance pipelines and reusable components, you will ensure that AI products are reliable, compliant, and capable of delivering next-generation experiences for both customers and employees. Responsibilities: Building and scaling next-generation Conversational AI platforms (voice and chat) using LLM-based agents and multi-agent orchestration frameworks. Developing automation agents for critical banking functions such as KYC, compliance, risk monitoring, and customer service. Implementing Retrieval-Augmented Generation (RAG) pipelines utilizing vector databases and knowledge graphs to power enterprise search. Model Optimization: Design and refine prompts to optimize LLM performance and apply advanced parameter-efficient fine-tuning techniques. Operationalizing embedding models and custom ML solutions by building APIs, SDKs, and CI/CD pipelines with automated retraining and drift management. Establishing engineering standards for model fairness, security, explainability, and disaster recovery to ensure operational resilience. Acting as an analytics translator, identifying opportunities for leveraging data to solve complex business problems across functional teams. Desired Candidate Profile What we need from you: 5+ years in AI/ML engineering or large-scale digital product engineering, ideally within a major digital transformation or digital-only bank project. Proven experience deploying large-scale AI/ML solutions within a regulated environment (Banking or Financial Services preferred). Hands-on experience with MLOps tools (MLflow, CI/CD) and data visualization platforms (Tableau, Power BI) Expert-level programming in Python specifically for ML/AI engineering and Generative AI applications. Deep knowledge of transformer models, multimodal architectures, and agentic AI systems (multi-agent frameworks/human-in-the-loop). Expertise in vector databases (Pinecone, Weaviate, Milvus), knowledge graphs, and both SQL/NoSQL systems (Postgres, MongoDB). Proficiency in Azure AI Foundry or AWS SageMaker, including serverless deployments (Lambda/Azure Functions) and containerization (Docker, Kubernetes). Deep understanding of LLM evaluation metrics and observability frameworks for monitoring agentic workflows. It would also be beneficial if you have experience of the following: Ability to quickly build and test AI prototypes while maintaining a focus on enterprise-grade security and compliance. Active engagement in the AI community with a track record of evaluating emerging tools like LangChain, CrewAI, and Bedrock. Exceptional communication skills to bridge the gap between technical requirements and business objectives for non-technical stakeholders. Deep understanding of emerging trends such as Reinforcement Learning from Human Feedback (RLHF) and multimodal AI. Company Industry ConsultingManagement ConsultingAdvisory Services Department / Functional Area IT Software Keywords Conversational AI Engineer Get real-time job updates only on our App