Quantitative Engineer - AI & Derivatives at Intercontinent… · London

Job Description

Intercontinental Exchange (NYSE:ICE) is a Fortune 500 company operating a leading network of global futures, equity, and equity options exchanges, alongside world-class clearing and data services spanning financial and commodity markets.We place the needs of our customers and global market participants at the forefront of everything we do. As a high-growth organisation, we pioneered transparency and risk management in global derivatives markets. Our team comprises engineers, strategists, and problem-solvers who continuously innovate technology solutions to address complex market structure challenges.About the RoleThe ICE Data Derivatives business provides market data, valuation, and analytics services across all OTC (over the counter) derivative asset classes to a global customer base.We are seeking an exceptional Financial Engineer to join our Pricing and Analytics team, a group dedicated to researching, implementing, and supporting enterprise-grade pricing and risk systems. This role requires a unique combination of quantitative finance expertise and cutting-edge AI capabilities, with particular emphasis on Deep Neural Networks and Large Language Models (LLM) applied to derivatives markets.Key****Responsibilities

• AI-Powered (artificial intelligence) Market Access: Design and deploy AI-driven conversational agents that enable clients to interact with derivatives market data and analytics through natural language interfaces, democratizing access to complex financial information.
• Neural Network Pricing Models: Research and implement Deep Neural Network-based approximations for exotic derivatives pricing models across Interest Rate, Equity, FX (forex), and Commodity asset classes, delivering order-of-magnitude improvements in computational performance for large, complex portfolios.
• Next-Generation Risk Analytics: Leverage advanced AI techniques to enhance risk management capabilities, including significant acceleration of Value-at-Risk (VaR) and XVA computations.
• Research & Documentation: Produce rigorous analysis and comprehensive documentation of AI methodologies, model architectures, and research findings to support transparency and knowledge transfer across the organization.
• Large-Scale Data Analysis: Extract insights from complex, high-volume datasets to inform model development and business strategy.
• Model Interpretation & Guidance: Provide clear explanations of AI model behavior, conduct scenario analysis, and deliver actionable analytics to stakeholders across the business.

Knowledge and Experience

• Expert professional experience in Machine Learning and quantitative finance.
• Demonstrated proficiency in modern AI development workflows, including fluency with tools such as Claude Code and GitHub Copilot.
• Proven ability to leverage Large Language Models for productivity enhancement across documentation, architecture design, and project development.
• Expert programming skills in C++.
• AI Agent Development: Demonstrated experience designing and deploying production-grade AI. agents utilizing Large Language Models, including prompt engineering, tool integration, and orchestration frameworks for autonomous decision-making systems.
• Deep Learning Architecture: Strong theoretical and practical knowledge of Deep Neural Network architectures, including feedforward networks, recurrent models, transformers, and their application to time-series forecasting and function approximation in financial contexts.
• Solid understanding of financial markets, derivatives pricing - risk modeling principles valued.

Core Competencies

• Hard worker and team player, highly self-motivated in learning and applying new techniques.
• Ability to solve real world business problems using AI and quantitative techniques.
• Strong oral communication and documentation skills.

Education

• Advanced degree (MSc OR PhD) in Mathematics, Physics, Quantitative Finance, Machine Learning, or any other related quantitative discipline/ equivalent.