AI Solution Architect M F D

Client of Talentmate

Leading Bank - Abu Dhabi, UAE

About The Role

Lead the design and implementation of enterprise-scale AI/ML and GenAI solutions at a premier Abu Dhabi bank. Drive the strategic vision for AI architecture, translating complex business requirements into scalable, secure, and compliant technical solutions.

Key Responsibilities

• Design and deploy AI/ML and Generative AI solutions at scale across diverse banking domains
• Translate business requirements into scalable technical architectures for AI/ML and GenAI use cases
• Lead end-to-end GenAI application design considering performance, cost, security, and scalability
• Design APIs, microservices, and system integrations across hybrid enterprise environments
• Orchestrate agentic workflows and manage complete LLM lifecycle including fine-tuning and versioning
• Collaborate with architects, cloud engineers, and security teams to ensure compliance and secure deployments
  
  

• Minimum 8 years in AI/ML roles, specialized in solutioning AI, ML and GenAI solutions
• Proven experience in designing and deploying AI/ML and Generative AI solutions at scale across diverse business domains
• Strong background in solutioning AI/ML and GenAI use cases, including translating business requirements into scalable technical architectures
  
  

• Experienced in designing APIs, microservices, and integrating systems across hybrid environments, aligned with enterprise architecture standards
• Demonstrated expertise in solutioning Conversational AI systems, including intelligent chatbots and virtual assistants powered by LLMs
• Builds and deploys intelligent agents and GenAI solutions using LLMs, integrating them with enterprise systems via APIs and event-driven architectures
• Leads end-to-end GenAI application design considering performance, cost, security, and scalability
• Orchestrates agentic workflows using tools like LangChain, Semantic Kernel, or custom layers
• Manages LLM lifecycle including fine-tuning, versioning, rollback, and secure access via enterprise identity systems
• Applies MLOps practices for scalable ML deployments and manages AI/ML model lifecycle including training, evaluation, and monitoring
• Designs AI/ML solutions using Azure or AWS, leveraging serverless architectures, cloud-native components, and cost optimization strategies
• Works closely with architects, cloud engineers, and security teams to ensure compliance, scalability, and secure deployments