Level

Multibank Group

AI Engineer – Generative AI and Automation

AI in this role

openaiclaudeanthropicgeminimistrallangchainllamaindexlanggraphcrewaiautogenhaystacksemantic-kernel+8
ragai-agentsml-opsai-automationai-safetyai-research

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

  • Multi-agent orchestration including planner, executor, critic, and memory agent patterns

  • Knowledge retrieval systems including enterprise RAG, document Q&A, and semantic search

  • Process automation integrating CRM, ERP, and communication tools end-to-end

  • Agent safety, guardrails, and human-in-the-loop oversight mechanisms

  • MCP server development for extending agent capabilities

Soft Skills

  • Strong problem-solving ability and analytical thinking

  • Ability to translate complex business needs into practical technical solutions

  • Effective collaboration and communication in a team-oriented environment

  • Intellectual curiosity and commitment to staying current with AI research and trends

Why Join Us?

  • Work with one of the world’s leading financial derivatives institutions.

  • Competitive salary plus performance-based incentives.

  • Access to a dynamic, international, and fast-growing environment.

  • Strong opportunities for career progression within a global financial group.

  • Be part of a business committed to innovation, excellence, and long-term growth.

Become part of our international community at MultiBank Group, dedicated to excellence, innovation, and shaping the future of finance.

MultiBank Group is an equal opportunity employer. We welcome applications from candidates of all backgrounds and do not discriminate on the basis of nationality, gender, age, religion, or disability.

How we rate this

AI Engineer – Generative AI and Automation at Multibank Group rates 96 out of 100 for how much of the daily work is AI. That makes it Builds AI (AI Level 4 of 4). The level is about AI in the job, not seniority.

Classification

Builds AI. The job is building AI systems.

  1. ●●●● Builds AI80 to 100
  2. ●●●○ Works on AI60 to 79
  3. ●●○○ Uses AI40 to 59
  4. ●○○○ Little AI0 to 39

Levels come from how often the tools, models and workflows of the role are named in the posting itself. Open the description and count.

Prepare for this job

A free preview built only from this posting: what it asks for, what you could be asked in an interview, and how to adjust your resume.

Skills and AI tools this role asks for

RAGAI AgentsML OpsAI AutomationAI SafetyAI ResearchOpenAIClaude

Questions you could be asked

  1. How would you design a retrieval step so the model answers from real data instead of guessing?
  2. How do you decide when an AI agent can act on its own versus asking for approval first?
  3. How do you monitor a model once it's live, and how do you know it needs retraining?
  4. Tell me about a workflow you automated with AI tools, end to end.
  5. How do you think about the risk of an AI system in this kind of role failing silently?

Adapt your resume

  • List these exact terms on your resume: RAG, AI Agents, ML Ops, AI Automation, and AI Safety. An applicant tracking system matches the wording, not the idea.
  • Attach one line of real, concrete experience to at least one of them — a tool named with nothing behind it rarely survives a human read.
  • Lead with what you built, trained or shipped — this role is judged on the AI system itself, not the tools around it.

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