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We are looking for a 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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