Low-Latency C++ Engineer: Exchange Connectivity

Tribus; Sydney; On-site; AUD 180,000 - 240,000; Full time

Benefits offered by this job

Competitive base salary

Performance-based bonus

Benefits package

Job summary

Tribus in Sydney is seeking an experienced C++ engineer to design and optimize high‑performance market data systems for real‑time trading. You’ll work on low‑latency exchange connectivity with direct impact on trading performance.

You’ll collaborate with quantitative researchers and trading technology teams, focusing on scalable, multi‑threaded architectures and efficient data processing from design through production deployment.

Qualifications

• 5+ years of experience developing high-performance C++ applications.
• Strong knowledge of multithreading, sockets, IPC, STL/Boost.
• Experience with profiling, performance tuning, and latency optimisation.
• Solid understanding of object-oriented design and software engineering principles.
• Proficient in Python and full software development lifecycle.

Responsibilities

• Develop low-latency market data and exchange connectivity systems.
• Profile, optimize performance, and reduce latency.
• Build multi-threaded and network-intensive applications.
• Create scalable systems supporting high-frequency trading strategies.
• Work on exchange feeds and market data infrastructure.
• Collaborate with quantitative research, infrastructure, and trading tech teams.
• End-to-end development from design through testing and production deployment.

Skills

C++

Multithreading

Sockets

IPC

STL/Boost

Profiling

OO Design

Python

SDLC

Problem Solving

Job description

Tribus in Sydney is seeking an experienced C++ engineer to design and optimize high‑performance market data systems for real‑time trading. You’ll work on low‑latency exchange connectivity with direct impact on trading performance.

You’ll collaborate with quantitative researchers and trading technology teams, focusing on scalable, multi‑threaded architectures and efficient data processing from design through production deployment.