We’re working closely with a high-performing quantitative trading firm to hire a Python Software Engineer for their core trading technology group. This team builds the systems that sit directly behind live strategies, research workflows, and execution infrastructure.
This role is best suited to engineers who enjoy deep technical ownership, care about performance and correctness, and want their work deployed in a real-time, production trading environment.
The Role
You’ll be developing and maintaining mission-critical software used across research, simulation, and live trading. The work is technically demanding and requires a strong understanding of software design, data, and systems — not just scripting.
You’ll collaborate daily with quant researchers and traders, translating research into reliable, well-engineered production code.
Key Responsibilities
Design and build high-quality Python systems used in live trading and research pipelines
Develop libraries and services for market data ingestion, back-testing, simulation, and execution
Optimise performance and reliability in a low-latency, high-throughput environment
Write well-tested, maintainable code with a strong emphasis on correctness
Contribute to system architecture, tooling, and engineering best practices
Core Technical Requirements
Strong professional experience with Python in production environments
Excellent understanding of data structures, algorithms, and software design principles
Experience working with large codebases and complex systems
Comfortable working in a Linux-based environment
Strong debugging, profiling, and performance-tuning skills
BSc or MSc in Computer Science or similar from a good university
Additional Languages (Nice to Have)
C++ (for performance-critical components)
Java or C# (backend or systems development)
Rust or Go (modern systems or tooling)
SQL and data-centric languages for analytics and research workflows
Nice to Have (But Not Required)
Exposure to quantitative finance, statistics, or time-series data
Experience with distributed systems, messaging, or event-driven architectures
Familiarity with cloud infrastructure, CI/CD, or containerised environments
Experience working closely with researchers, scientists, or highly technical end users