Crypto.com

AI Engineer (Trading Ops & Management)

In short

AI Engineer role at a crypto trading company, managing multi-asset trade lifecycles and automating operational workflows and reconciliations using agentic AI, Python, and MLOps tools. The role covers P&L attribution, variance investigation, anomaly-detection agents, and real-time risk models with risk-reporting dashboards. Requires 3+ years in front-office operations, quant development, or risk management at a financial institution, expert Python, and strong SQL skills. Hybrid role based in London, with readiness to work extended hours to meet global trading demands.

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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