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Trading Ops & Risk Systems Engineer; AI & Automation
Job in
Greater London, London, Greater London, W1B, England, UK
Listed on 2026-01-24
Listing for:
P2P
Full Time
position Listed on 2026-01-24
Job specializations:
-
IT/Tech
Data Scientist -
Finance & Banking
Data Scientist
Job Description & How to Apply Below
Location: Greater London
We are seeking a highly analytical and technical professional to spearhead the evolution of our trading infrastructure. This hybrid role combines the fast-paced execution of a Trading Operations Specialist, the analytical rigor of a Risk Manager, and the technical capabilities of an AI-focused Developer.
The successful candidate will not only manage daily operational workflows and risk monitoring but will also lead the digital transformation of these functions. You will leverage Large Language Models (LLMs), machine learning, and advanced scripting to automate legacy manual processes, improve predictive risk modeling, and build real-time P&L visualization tools.
Key Responsibilities:- Trading Operations and P&L Analysis with AI:
Manage the end-to-end lifecycle of trades across multi-asset classes. Develop agentic AI workflows using Python (ML) and MLOps tools to automate manual operations and reconciliations - Perform daily P&L attribution and explain variance by decomposing market moves, Greeks, and new activity. Leverage AI/ML frameworks (e.g., OpenAI API, Lang Chain, or local LLMs) to build intelligent agents for anomaly detection in trade data and automated commentary generation for P&L reports.
- Ensure data integrity across trading systems, middle-office platforms, and downstream finance ledgers.
- Risk Monitoring & Control:
Intelligent
Risk Management:
Develop real-time, AI-driven risk models that use machine learning to predict market volatility and alert the desk to emerging cross-market risks. - Develop and maintain sophisticated risk reporting dashboards for the desk.
- Experience:
5+ years in front-office operations, quant development, or a blend of risk management and systems architecture within a financial institution. - Technical Stack:
Expert proficiency in Python (for AI/ML), and strong SQL skills. Experience building agentic AI workflows is a significant advantage. - Financial Acumen:
Deep understanding of P&L attribution, financial controls, market risk indicators (Greeks, VaR), financial markets and products. - Problem Solving: A "systems-thinking" approach to operations—treating every manual task as a bug that needs an automated solution.
- Capacity:
Ability to thrive in a high-intensity environment requiring extended hours (eg. 60-70/week) to meet global trading demands. - Agility:
Willingness to participate in a rotational weekend and 24/7 on-call schedule, providing immediate resolution to live production issues
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