Talantix.io
Crypto.com•14.02.26
AI SCORE 8.7

Trading Ops & Risk Systems Engineer (AI & Automation) - Remote

$140K–$180K/year
RemoteCrypto/Web3
Python•Machine Learning•SQL•Risk Management•AI Workflows•Data Analysis

About the Role

We are seeking a highly analytical and technical professional to join us as a Trading Ops & Risk Systems Engineer (AI & Automation) remote. 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. You will manage daily operational workflows and risk monitoring while leading the digital transformation of these functions.

What You'll Do

  • Manage the end-to-end lifecycle of trades across multi-asset classes, ensuring data integrity across trading systems.
  • Develop agentic AI workflows using Python and MLOps tools to automate manual operations and reconciliations.
  • Perform daily P&L attribution, explaining variance by decomposing market moves, Greeks, and new activity.
  • Leverage AI/ML frameworks to build intelligent agents for anomaly detection in trade data and automated commentary generation for P&L reports.
  • Develop real-time, AI-driven risk models that predict market volatility and alert the desk to emerging cross-market risks.
  • Maintain sophisticated risk reporting dashboards for the desk.

Requirements

  • 5+ years in front-office operations, quant development, or a blend of risk management and systems architecture within a financial institution.
  • Expert proficiency in Python for AI/ML, and strong SQL skills.
  • Experience building agentic AI workflows is a significant advantage.
  • Deep understanding of P&L attribution, financial controls, market risk indicators, and financial markets.
  • A systems-thinking approach to operations, treating every manual task as a bug needing an automated solution.
  • Ability to thrive in a high-intensity environment requiring extended hours to meet global trading demands.
  • Willingness to participate in a rotational weekend and on-call schedule, providing immediate resolution to live production issues.

Nice to Have

  • Experience with Large Language Models (LLMs) and advanced scripting.
  • Strong analytical skills and problem-solving capabilities.
  • Familiarity with financial products and market dynamics.

What We Offer

  • Competitive salary and benefits package.
  • Remote work flexibility with opportunities for career growth.
  • Access to cutting-edge technologies and tools.
  • Dynamic and collaborative work environment.
  • Support for continuous learning and professional development.
Why This Job8.7 of 10

This role offers a unique blend of trading operations and AI automation, making it ideal for candidates looking to innovate in the finance sector. Competitive salary and remote work add to its appeal.

Salary Range
Required
0/1
Optional
0/1
Bonus
0/1

Who Will Succeed Here

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Proficient in Python and SQL with hands-on experience in developing AI workflows and automating risk management processes, ensuring efficient trading operations.

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Strong analytical mindset with a proven track record in data analysis and risk assessment, capable of identifying and mitigating risks in high-frequency trading environments.

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Self-motivated and adaptable, thriving in a fully remote work environment, demonstrating excellent time management and the ability to prioritize tasks in a fast-paced, dynamic setting.

Learning Resources

→Python for Data Analysiscourse
→Machine Learning with Python: From Linear Models to Deep Learningcourse
→Understanding Risk Management in Tradingarticle

Career Path

Trading Ops & Risk Systems Engineer (AI & Automation)(Now)→Senior Risk Analyst / AI Automation Lead(1-2 years)→Director of Trading Operations / Head of Risk Management(3-5 years)

Market Overview

Market Size 2024
$5.6B
Annual Growth
22.4%
AI Adoption in Finance
75%
Investment in AI & Automation
+45%
Labour Demand for Python Engineers
+30%
Avg Salary for Trading Ops Engineers
$130K

Skills & Requirements

Required
PythonMachine LearningSQL
Growing in Demand
Data EngineeringCloud Computing (AWS/Azure)Advanced Analytics
Declining
R (for Data Analysis)Excel for Risk Management

Domain Trends

Rise of AI in Trading
AI-driven trading algorithms are expected to increase trading efficiency by 40% by 2025, leading to a surge in demand for engineers skilled in AI and automation.
Integration of Machine Learning in Risk Management
Over 60% of financial firms are integrating machine learning models into their risk management processes to enhance predictive accuracy and reduce operational risks.
Shift towards Cloud-Based Risk Systems
By 2025, 70% of financial institutions will have migrated their risk management systems to the cloud, creating a demand for engineers with cloud computing skills.

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