AI Engineer – Generative AI and Automation

Welcome to Multi Bank 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, Multi Bank Group is devoted to innovation, excellence, and empowering our clients to achieve their financial goals.

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.

• 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 Lang Chain, Lang Graph, CrewAI, Auto Gen, 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

• 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 Lang Chain, Lang Graph, 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 Type Script is beneficial
• Familiarity with cloud platforms, Docker, FastAPI, and CI/CD practices for AI pipelines

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

Agent Frameworks
:
Lang Chain, Lang Graph, CrewAI, Auto Gen, Semantic Kernel, Haystack

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

Vector Databases and RAG: Pinecone, Weaviate, Qdrant, pgvector, Chroma, Llama Index

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

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

Observability and Evaluation: Lang Smith, Helicone, Weights and Biases, custom evaluation harnesses

AI Agent Focus Areas

• Autonomous and semi-autonomous agents for customer service, operations, marketing, and data analysis
• Multi-agent orchestration including planner, executor, critic, and memory…