Senior C++ Trading Systems Engineer / Quant Developer
A senior C++ engineer to take ownership of a live systematic CME futures stack, built in-house and already trading NQ, ES, gold and oil. You'll harden it, make the backtests honest and take trading-system decisions off the person who built it. Real architectural say, and a route closer to strategy, execution and P&L than a C++ seat inside a large institution would give you.
The work
The research and engineering arm of a privately funded investment group runs systematic strategies on CME futures from a stack it built itself: a commercial market data feed, a custom C++ and LMDB trading database, QuickFIX broker connectivity, Docker and GitLab deployment, and leased infrastructure in Chicago. The engineering foundation is real. The next step is to make the trading capability more reliable, safer to scale and less dependent on one person. You will join a small, high-trust R&D team led by the Head of AI, who built the platform from scratch and has a background in low-latency, high-throughput C++. This is not a generic software role and not a pure quant research role. It sits between trading systems engineering, execution, market data, backtesting, risk controls and live production judgement.
What you'll own
Production hardening, backtesting realism, order handling, broker connectivity, market data workflows, risk controls, release discipline and the design decisions that decide how the platform scales.
- Own or co-own the order processor, execution simulator, market data storage, backtesting framework, risk controls, reconciliation and recovery
- Make backtests more honest by accounting for fills, spread, volume, latency, execution constraints and regime change
- Strengthen live-trading safety through limits, kill switches, monitoring, logging, state recovery and operational discipline
- Turn research ideas into production-ready trading capability, working closely with the Head of AI and the wider team
- Bring clearer engineering structure to a small environment without slowing it down with unnecessary process
- Over time, take more trading-system decisions off the platform's builder and help define the next stage of the trading function
What you'll need
You do not need to be a quant researcher, but you do need enough trading judgement to understand why software behaviour matters when it drives orders, exposure and P&L. CME futures, Databento, LMDB, QuickFIX, Interactive Brokers, Python, Docker, GitLab and Linux are all useful, but not essential. This will not suit someone who needs a large platform, a narrow remit, a fully specified ticket queue or a big-fund brand around them.
- Recent production C++ where correctness, latency, state and reliability matter, not academic or legacy exposure
- Experience in or close to trading: OMS, EMS, execution engines, FIX, market data, exchange or broker connectivity, backtesting infrastructure or risk systems
- Comfort reasoning about concurrency, latency, state, debugging, testing and production failure modes
- The ability to draw and explain systems you personally built or owned
- A clear view of how backtests mislead: leakage, overfitting, look-ahead bias, unrealistic fills, survivorship bias and regime change
- The judgement to work where ownership is broad and decisions cannot always be escalated
The package
Base up to £90,000, plus a discretionary profit-based bonus shared across the group. Remote-first, with a London-based team that meets regularly in person. You can keep developing and trading your own ideas under the group's dealing policy, provided company information and IP stay separate.
What happens next
We start with a confidential conversation about the stack, the team and where the trading function is heading. The process is an introductory call, a technical deep dive, an architecture discussion and a final meeting with the leadership team.
If it is a fit, you will get a straight read on the process and the comp. If it is not, I will tell you that too.