Senior Software Engineer
Python Distributed Systems Engineer – Quantitative Trading Technology
Location: London
Compensation: Circa £250,000 Total Compensation (Base + Bonus)
Company:
I’m currently working with a global-leading multi-strat investment firm operating at scale — thousands of strategies, millions of data points per second, sitting at the intersection of technology and quantitative research. They build cutting-edge distributed systems that power real-time trading, risk management, and data analytics across global markets.
The Role:
Currently looking for an exceptional Python Engineer to design, implement, and optimize distributed systems that underpin the global quantitative trading platform.
You’ll work alongside world-class developers, quantitative researchers, and infrastructure experts to build low-latency, fault-tolerant, and highly scalable systems. This is an opportunity to work on projects where milliseconds and megabytes matter — and where your code directly contributes to business performance.
What You’ll Do
- Architect and implement distributed data pipelines and compute frameworks in Python
- Build services that handle high-throughput event streams and large-scale time-series data
- Collaborate with quant teams to integrate new datasets, models, and analytics tools
- Optimize performance for latency, throughput, and reliability
- Contribute to the continuous evolution of our engineering culture — automation, CI/CD, observability, testing
What We’re Looking For
- 4+ years of experience in Python (asyncio, multiprocessing, FastAPI, or similar frameworks)
- Solid understanding of distributed systems concepts : messaging, consensus, data partitioning, fault tolerance
- Experience with technologies such as Kafka, Redis, gRPC, Kubernetes, Ray, or Dask
- Strong background in Linux environments and performance tuning
- A passion for clean code, automation, and technical excellence
- Exposure to financial data, trading systems, or high-frequency environments is a strong plus
Please contact daniel.mclagan@stanfordblack.com for more information.
If this role isn't right for you, but you know of someone who might be interested, we have a market-leading referral scheme in place to thank anyone who refers a friend who is successfully placed! T&Cs apply.