About the role
We are looking for a deeply technical and mathematically minded Product Manager to join and help scale our expanding Risk Tech team.
In a high-frequency, high-volume trading platform processing billions in volume across CFD, Crypto Spot, and Derivatives, Risk Tech is both the ultimate line of defense and a core driver of platform stability. As a Product Manager in this domain, you will drive the product strategy for real-time margin engines, exposure aggregation (A/B/C-book), microsecond anti-fraud protection, and portfolio risk management. You will act as the crucial bridge between Quantitative Analysts, Head of Risk & Dealing, and Systems Engineers building lock-free, low-latency backend architectures.
If you thrive at the intersection of quantitative finance, low-latency engineering, and capital protection, this role is for you.
Responsibilities • Drive the product vision, technical roadmap, and PRDs for key areas within the Risk Tech domain (Margin Engines, Exposure Management, Anti-Fraud, Derivatives Risk, Stress Testing) • Parter with Quants and the Head of Risk & Dealing to translate mathematical risk models (Monte Carlo, VaR, Volatility Surfaces) into deterministic algorithms for high-performance engineering teams • Define edge-case handling rules for Black Swan scenarios, exchange de-pegging, and cascading liquidation events • Collaborate with Dealing and Trading Ops teams to deliver high-performance internal admin tools, real-time risk monitors, and override APIs • Conduct post-incident deep dives following major market movements to continuously optimize risk parameters and engine performance
Requirements • 3+ years of Product Management experience in Risk Tech, Quantitative Trading, Crypto Derivatives Exchanges, or CFD Brokerages • Deep knowledge of financial risk mechanics: Cross/Isolated Margin, Portfolio Margin, A/B/C-book operating models, Net Open Position (NOP) aggregation, and options risk metrics • Solid understanding of low-latency backend architecture: lock-free concurrency, In-Memory data processing, IPC/Shared Memory, and financial protocols (FIX, WebSocket) • Strong understanding of market microstructure, order book dynamics (L2/L3), matching engine mechanics, and liquidity bridging/routing
Will be a plus • Proficiency in quantitative analysis concepts and data architectures: Python/SQL for risk modeling, time-series databases (ClickHouse), and Big Data processing • Academic background in Quantitative Finance, Applied Mathematics, Computer Science, or Financial Engineering • Practical familiarity with low-latency programming languages (C++, Rust, or C#) • Direct experience with crypto-native liquidation mechanisms or options pricing models
We offer • 20 paid vacation days per year • 10 paid sick leave days per year • Public holidays as per the company's approved Public holiday list • Medical insurance • Opportunity to work remotely • Professional education budget • Language learning budget • Wellness budget (gym membership, sports gear and related expenses)
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