Product Manager (Risks)

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)

Role mission

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 key 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.

1. Role Mission
To co-own, scale, and maintain an ultra-low latency, deterministic Risk Tech architecture that protects exchange capital from bad debt, toxic flow, and market volatility. The global need is to deliver sub-millisecond risk evaluations and automated risk actions without introducing backpressure or execution latency to the core Matching Engine.

Requirements soft skills

Zero-Tolerance Mindset: Extreme rigor regarding mathematical logic and system edge cases, knowing that a single oversight can lead to severe capital loss.

Cross-Disciplinary Translation: Ability to translate complex mathematical abstractions and risk policies into clear technical specifications for backend software engineers.

Composure Under Pressure: Ability to remain calm, analytical, and decisive during flash crashes, high-volatility events, or system-level risk incidents.