AI Engineering Lead – LLM Engineering, AI Development & Intelligent Automation

Welcome to MultiBank Group , a global financial pioneer established in 2005 in California and now proudly headquartered in Dubai, UAE. We specialize in delivering cutting-edge trading technology, unparalleled liquidity, and exceptional customer service. Our extensive range of financial products includes Forex, Metals, Shares, Indices, Commodities, and Cryptocurrency CFDs.

Join our thriving community of over 2 million clients across 100 countries, contributing to a daily trading volume exceeding US$ 35 billion. As a heavily regulated institution with oversight from 18+ financial regulators across 5 continents, and recipient of over 80 financial awards, MultiBank Group is devoted to innovation, excellence, and empowering our clients to achieve their financial goals.

Role Overview

We are looking for an experienced AI Engineering role to drive the organization's LLM Engineering capability and accelerate AI-powered software development across multiple technology teams.

You will establish engineering standards for building AI-native software, guide development teams on effectively leveraging frontier LLMs, introduce AI-assisted software engineering practices, and define the enterprise roadmap for intelligent application development.

You will work closely with engineering managers, architects, product owners, and leadership to ensure every development team successfully adopts modern AI engineering practices using tools such as Claude Code, OpenAI Codex, Cursor, Gemini CLI, GitHub Copilot, Windsurf, and emerging AI development platforms.

You will also lead the design of enterprise-grade AI systems, supervise implementation of agentic architectures, establish an AI Engineering Maturity Model, and mentor teams in delivering production-ready AI solutions at scale.

Key Responsibilities

AI Development Supervision

• Guide and mentor software engineering teams in building AI-native applications.
• Review architecture, code quality, prompting strategy, agent design, and AI implementation approaches.
• Conduct AI solution design reviews before development begins.
• Coach engineers on AI-first development methodologies and modern software delivery practices.
• Ensure projects leverage AI effectively to reduce delivery timelines while maintaining software quality.

AI-Assisted Software Engineering

• Champion AI-powered development using Claude Code, Cursor, GitHub Copilot, Gemini CLI, Windsurf, OpenAI Codex, and similar AI development environments.
• Define enterprise standards for Vibe Coding and AI-assisted software engineering.
• Establish best practices for prompt engineering for developers.
• Design reusable prompt libraries and engineering playbooks.
• Measure and improve developer productivity using AI.

LLM Engineering

• Design, build, and optimize production-grade LLM applications.
• Develop intelligent AI agents using Claude, OpenAI, Gemini, Mistral, and other frontier models.
• Build multi-agent systems using LangGraph, LangChain, CrewAI, AutoGen, and Semantic Kernel.
• Implement enterprise RAG systems using vector databases and knowledge graphs.
• Design scalable MCP (Model Context Protocol) servers and tool integrations.
• Evaluate new LLMs and recommend adoption strategies.

AI Platform & Architecture

• Define enterprise AI architecture standards.
• Build reusable AI components and internal AI platforms.
• Design secure integrations between LLMs and enterprise systems.
• Define guardrails, evaluation frameworks, observability, and responsible AI practices.
• Lead technical decision-making for AI infrastructure and deployment.

AI Capability Development

• Conduct internal workshops on AI engineering tools and best practices.
• Train development teams on AI coding assistants and LLM engineering workflows.
• Develop int