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 a Senior AI Architect to design, build, and scale the AI and data platform that the organization's AI products will run on. This is a hands-on, founding technical position. The Senior AI Architect will produce architecture designs, write production code, build data pipelines, and set the engineering standards the broader AI team will follow. The role requires rare technical breadth: deep data engineering foundations, strong software engineering discipline, AI and ML systems experience, cloud infrastructure fluency, and the architectural vision to make it all coherent at enterprise scale.

Key Responsibilities

Design and build the end-to-end AI platform architecture, covering data ingestion, feature engineering, model training, serving, monitoring, and retraining as a coherent, maintainable production system

Design the data lakehouse architecture on AWS using Delta Lake or Apache Iceberg with Databricks as the primary compute layer, and build batch and streaming data pipelines using PySpark, AWS Glue, and Kafka

Architect and implement a feature store with online and offline stores, point-in-time joins, and feature versioning

Own cloud infrastructure architecture for all AI and data workloads on AWS, including multi-account strategy, EKS cluster design, GPU compute, storage, and cost governance

Build and own the MLOps platform covering experiment tracking, training pipeline automation, model packaging and deployment standards, CI/CD for ML, and model monitoring with drift detection

Design the AI services layer, including reusable inference APIs, model serving infrastructure, and API gateway configuration with authentication, rate limiting, and cost attribution

Integrate AI capabilities into the organization's products and business systems using event-driven and API-based patterns

Embed security and compliance into every layer of the AI platform, including network security, IAM, PII handling, secrets management, and audit logging

Act as the senior technical authority for the AI Initiative, setting engineering standards, mentoring engineers, and leading technical decisions

Produce and maintain architecture documentation including C4 diagrams, Architecture Decision Records, and system integration maps

Requirements

15 or more years of experience spanning data engineering, software engineering, and AI/ML systems, with at least 3 to 5 years in a senior architecture role

Demonstrable record of building and shipping production AI systems end-to-end, not solely designing them

Deep hands-on data engineering background including production data pipelines, data lakehouses, and feature stores

Expert-level AWS skills across multi-service architecture design and build; GCP or Azure familiarity is beneficial

Strong software engineering discipline with production-quality Python and SQL, and solid understanding of distributed systems and API design

Deep understanding of the AI and ML model lifecycle and the infrastructure required to support it at production scale

Experience in high-growth product companies, scale-ups, or enterprise AI teams where significant technical decisions were owned

Security-conscious approach as a default, with experience embedding data privacy and compliance requirements into architecture