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April 29, 2026

Java Developer | FX & Commodities Trading Platform |

Senior • Remote

2,100 - 2,500 PLN

**CANDIDATES MUST HAVE FINANCIAL EXPERIENCE**

Java Engineer – FX & Commodities Risk Platform 

Global Investment Bank | Low‑Latency Systems | B2B | Remote | Rate: 2100PLN + | Must have Financial Experience

A global investment bank is expanding its FX & Commodities Risk engineering team and is hiring a Senior Java Engineer in Poland to help build a next‑generation risk platform used by trading desks in London, Singapore, and New York.

This is a rare opportunity to work on a brand‑new system rewrite while learning from a complex, high‑performance legacy platform that has powered global trading for years.

What We’re Looking For

  • Strong experience with Core Java and Spring

  • Solid understanding of multithreading, concurrency, and low‑latency systems

  • Experience with Kafka, Hazelcast, or similar distributed technologies

  • Familiarity with modern data stores (ClickHouse is a plus)

  • Ability to learn from and navigate complex legacy systems

  • Proactive mindset — someone who can drive development forward

  • Strong communication and collaboration skills

  • FX Risk or broader trading‑systems experience is a strong plus

About the Platform
The FX & Commodities Risk Platform provides real‑time risk calculations and reporting across multiple asset classes. The current system includes:

  • Frontend: WPF (C#)

  • Backend: Java (Core Java, Spring)

  • Quant Library: In‑house, with Haskell used for interaction

A full rewrite is underway, moving the platform to a modern, scalable architecture.

What You’ll Work On
You’ll play a key role in building the new platform, which is moving towards:

  • Spring Boot

  • Kafka for event streaming

  • Hazelcast for distributed caching and computing

  • ClickHouse for high‑performance data storage and reporting

Key Engineering Focus Areas

  • High‑performance multithreading & concurrency

  • Low‑latency backend development

  • Distributed systems using Kafka and Hazelcast

  • Data‑intensive workloads using ClickHouse

  • Interacting with the quant library (light Haskell exposure)

  • Learning from the legacy system’s memory‑optimised design (critical for JVM stability)

This is a backend‑heavy role with deep engineering challenges.