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)
