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 seeking an AI Engineer to design, build, and deploy intelligent AI agents and automated workflows that address real business problems. This is a hands-on, high-impact role within the Artificial Intelligence and Advanced Analytics team. The successful candidate will own end-to-end delivery of AI agents from scoping and architecture through integration, testing, and production deployment, enabling the organization to automate complex processes and unlock value from generative AI.

Key Responsibilities

Design, build, and deploy AI agents using frontier LLMs including Claude (Anthropic API), OpenAI, Gemini, and other frontier models

Architect multi-agent systems and agentic workflows using frameworks including LangChain, LangGraph, CrewAI, AutoGen, and Semantic Kernel

Build and manage automated business workflows using n8n, Make (Integromat), Zapier, and custom API integrations

Implement RAG pipelines with vector databases including Pinecone, Weaviate, Qdrant, and pgvector to give agents access to organizational knowledge bases

Design tool-use and function-calling integrations, connecting agents to internal systems, APIs, databases, and third-party services

Fine-tune and prompt-engineer LLMs to optimize agent behavior, reliability, and task accuracy

Collaborate with business stakeholders to identify automation opportunities and translate requirements into agent-based solutions

Monitor, evaluate, and continuously improve deployed agents across quality, latency, cost, and safety metrics

Establish and maintain best practices for agent safety, guardrails, human-in-the-loop controls, and responsible AI deployment

Develop MCP (Model Context Protocol) server integrations to extend agent capabilities

Requirements

Bachelor's or Master's degree in Computer Science, Artificial Intelligence, Software Engineering, or a related field; equivalent practical experience will be considered

2 or more years of hands-on experience building production AI systems or intelligent automation solutions

Demonstrated experience building agents or workflows with LangChain, LangGraph, CrewAI, n8n, or comparable frameworks

Proven ability to integrate LLM APIs including Anthropic Claude and OpenAI into real-world applications

Experience with vector databases and semantic search implementations is strongly preferred

Portfolio or demonstrable projects showing deployed agents, automation workflows, or RAG-based applications

Proficiency in Python as the primary language; JavaScript or TypeScript is beneficial

Familiarity with cloud platforms, Docker, FastAPI, and CI/CD practices for AI pipelines

Technical Skills

LLM APIs: Anthropic Claude (claude-opus-4, claude-sonnet-4), OpenAI GPT-4o, Google Gemini, Mistral

Agent Frameworks: LangChain, LangGraph, CrewAI, AutoGen, Semantic Kernel, Haystack

Workflow Automation: n8n, Make (Integromat), Zapier, Apache Airflow

Vector Databases and RAG: Pinecone, Weaviate, Qdrant, pgvector, Chroma, LlamaIndex

Programming: Python (primary), JavaScript/TypeScript, REST API design

Cloud and MLOps: AWS, Azure, GCP, Docker, FastAPI, CI/CD for AI pipelines

Observability and Evaluation: LangSmith, Helicone, Weights and Biases, custom evaluation harnesses

AI Agent Focus Areas

Autonomous and semi-autonomous agents for customer service, operations, marketing, and data analysis