Trading Ops Risk Systems Engineer AI Automation
## Key Responsibilities:
1. 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, LangChain, 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.
2. 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.
## Requirements & Qualifications
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.
• *If you’re passionate about blockchain and decentralized technologies, explore more opportunities in web3 and cryptocurrency careers.**
Apply Now
Apply Now
1. 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, LangChain, 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.
2. 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.
## Requirements & Qualifications
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.
• *If you’re passionate about blockchain and decentralized technologies, explore more opportunities in web3 and cryptocurrency careers.**
Apply Now
Apply Now