Provn are proud to be partnered with a boutique systematic hedge fund as they look to hire a Quant Developer to join their Trading Technology team in London.

Our client is a highly regarded, technology-driven investment firm operating at the forefront of systematic trading. They are continuing to invest in their core trading platform to support scalable research, robust execution, and increasingly sophisticated systematic strategies.

The Trading Technology team sits at the intersection of quantitative research and live trading, building and maintaining the systems that enable models to move seamlessly from research into production. This role offers a strong blend of hands‑on engineering, platform ownership, and close collaboration with researchers and traders.

This is a high‑impact opportunity suited to engineers who thrive in complex, fast‑paced environments - individuals who enjoy building distributed systems, optimising performance, and taking ownership of critical trading infrastructure.

Key Responsibilities:

• Design, build, and enhance core trading and research platforms supporting:
• Strategy research and backtesting workflows
• Real‑time trading and execution systems
• Market data ingestion and processing pipelines
• Develop scalable, robust systems using Python (research/model integration) and Java (core platform engineering), with some exposure to C++ where required
• Work closely with quantitative researchers and trading teams to translate models into production‑ready systems
• Contribute to the design and implementation of distributed, event‑driven architectures using technologies such as Kafka and containerised environments
• Optimise system performance across both research and live trading environments, focusing on latency, throughput, and scalability
• Take ownership of production systems, including:
• Monitoring and reliability improvements
• Troubleshooting and incident resolution
• Continuous performance tuning
• Contribute to modernisation initiatives, including cloud‑based infrastructure (e.g. Kubernetes) and system rearchitecture
• Write clean, maintainable, well‑tested code and contribute to CI/CD and release processes
• Participate in architectural discussions, design reviews, and long‑term technical planning

Role Requirements:

• Strong software engineering background with experience in both research and production/trading environments
• Proficiency in Python and Java, with additional experience in C++ beneficial
• Solid understanding of distributed systems, messaging frameworks (e.g. Kafka), and scalable system design
• Experience with containerisation and cloud technologies (e.g. Kubernetes)
• Strong focus on performance optimisation (system‑level, not just quantitative models)
• Comfortable working across the full lifecycle: development, deployment, and production support

Preferred Experience:

• Background in systematic trading, asset management, or investment banking
• Exposure to quantitative research workflows or model implementation
• Understanding of financial markets, instruments, and trading concepts
• Experience building or supporting trading platforms or market data systems

The Ideal Candidate:

The ideal candidate combines strong engineering fundamentals with experience in trading environments, and the ability to bridge the gap between research and production. They will be comfortable working closely with both quants and traders, while taking ownership of complex, business‑critical systems.

Why Apply:

• Opportunity to join a high‑performing, technology‑led systematic hedge fund
• Work on core trading systems with direct impact on research and execution
• Strong balance of engineering depth, system ownership, and business interaction
• Collaborative, high‑calibre environment focused on performance, scalability, and innovation

Comp: