Head of Artificial Intelligence

Location: Paris, Geneva or Dubai

Firm Overview

BGC is a leading global brokerage and financial technology firm that specializes in brokering a broad range of products and asset classes, as well as provides a variety of back-office services and technology-driven solutions to customers across the world. Its technology platforms support clients across global markets through tools, market data, and analytics that enhance price discovery and trade execution with respect to numerous financial instruments and markets.

Responsibilities

This is a senior leadership role covering the design, delivery, and adoption of AI-powered solutions across EMEA. The right candidate can demonstrate a track record of delivered and successful AI within their current organization — defining strategic direction, building at the frontier, and driving measurable business impact across multiple workstreams simultaneously – and:

• Lead the end-to-end lifecycle of AI initiatives — from problem identification and architecture through production deployment, enablement, and continuous improvement
• Partner with C‑Suite and front‑office teams to translate complex business challenges into production‑grade AI products
• Manage solution quality and program performance
• Track adoption, usage, and business outcomes of deployed tools
• Design and operate the enablement infrastructure — training, documentation, support channels, and feedback loops — that drives sustained adoption at scale
• Manage the regional demand pipeline: intake, prioritization, scoping, and transparent stakeholder communication

Qualifications

• Bachelor's degree required; CS, engineering, or data science preferred.
• 5+ years in product, technology, or data roles with progressively expanding ownership.
• Required Technical Knowledge and Proficiencies:
  • LLM system architecture — context engineering, evaluation frameworks, guardrails, agent workflows, and cost/quality tradeoff analysis
  • API design and systems integration — RESTful APIs, microservices, data pipelines, and cloud infrastructure (AWS/Azure/GCP)
  • Full‑stack prototyping — ability to build end‑to‑end from data layer through application logic to user interface
  • MLOps and production monitoring — CI/CD, model performance tracking, and iterative improvement based on real usage data
  • AI deployment in regulated environments — model risk management, auditability, data sensitivity controls, and compliance‑aware design
• Demonstrated ability to drive adoption and behavior change across teams without direct reporting authority.
• Comfortable navigating compliance, data sensitivity, and regulatory constraints inherent to global financial services.