Назад
5 дней назад

AI Engineer (Trading Ops & Management)

Формат работы
hybrid
Тип работы
fulltime
Грейд
senior
Страна
UK
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Описание вакансии

TL;DR
AI Engineer (Trading Ops & Management) (AI/ML and financial trading operations): Automating multi-asset trade lifecycles, reconciliations, reporting, and risk management with an accent on agentic AI, Python, MLOps, and financial controls. Focus on building anomaly-detection agents, performing P&L attribution, developing real-time risk models, and maintaining risk-reporting dashboards.

AI Engineer Trading Ops & Management

Company

Crypto.com

Conditions

4 days ago

Skills

Candidate Availability

Required and preferred rules are kept separate and reflect the wording in the original posting.

About the Role

You will manage trade lifecycles across multi-asset classes and automate operational workflows and reconciliations using agentic AI, Python, and MLOps tools. You will perform P&L attribution, investigate variance, ensure data integrity across trading and finance systems, and build AI-assisted reporting and business analyses. You will also develop real-time risk models, identify emerging cross-market risks, and maintain risk-reporting dashboards.

Requirements

  • 3+ years of experience in front-office operations, quant development, or risk management and systems architecture within a financial institution
  • Expert proficiency in Python for AI and machine learning
  • Strong SQL skills
  • Understanding of P&L attribution, financial controls, market risk indicators, financial markets, and products
  • Systems-thinking approach to automating manual tasks
  • Ability to work extended hours when necessary to meet global trading demands

Responsibilities

  • Manage the end-to-end lifecycle of trades across multi-asset classes
  • Develop agentic AI workflows to automate manual operations and reconciliations
  • Perform daily P&L attribution and explain variance
  • Build AI agents for trade-data anomaly detection and P&L-report commentary
  • Ensure data integrity across trading systems, middle-office platforms, and finance ledgers
  • Build reporting and analyses on trading performance
  • Develop real-time AI-driven risk models
  • Develop and maintain risk-reporting dashboards

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