Senior Backend & Kubernetes Engineer — Global Quant Fund : London : £200-300k

We are partnering with one of the world's most technically rigorous quantitative investment firms to identify an exceptional Senior Backend Engineer with deep expertise in Python, Kubernetes, and distributed systems. This is an opportunity reserved for engineers who operate at the very highest level of technical execution. Our client runs a lean, elite engineering organisation where impact is immediate, autonomy is real, and engineering excellence is non-negotiable.

Core Technical Focus

• Python — production-grade backend engineering, clean architecture, high-performance systems.
• Kubernetes — expert-level understanding of container orchestration, scaling strategies, service deployment, and cluster operations.
• Distributed Systems — designing, building, and maintaining scalable, fault-tolerant services for data and compute-intensive workloads.
• Airflow & workflow schedulers — (Airflow or similar free-flow/scheduler frameworks) for orchestrating complex pipelines.
• 5+ years of hands-on engineering experience in high-performance, modern backend environments.

Profile We're Targeting

This fund thrives on engineering pragmatism, velocity, and precision. They do not favour traditional big-bank engineering backgrounds with heavy bureaucracy and legacy technology.

Instead, they value:

• Startup or scale-up environment experience
• Engineers who have built systems end-to-end, not just maintained them
• People who are hands-on, deeply technical, and take ownership of problems
• Strong operational awareness and an ability to build robust, production-grade systems in lean, fast-moving teams
• Computer Science or similar type degree from a good university

Role Overview

• Build and optimise large-scale distributed backend services that underpin quant research and production trading.
• Own Kubernetes-based deployments and orchestration frameworks across highly customised environments (often on-prem).
• Develop reliable and elegant Python services that support high-throughput data, compute, and model execution pipelines.
• Architect and maintain Airflow / scheduler-based workflows critical to research and production operations.
• Collaborate directly with world-class researchers, data teams, and platform engineers to drive performance and reliability across the stack.
• This role does not involve developing machine learning models — instead, you'll architect the systems that allow them to run flawlessly.

Why This Role Is Elite

• Engineering-first culture with zero tolerance for mediocrity
• High autonomy, minimal bureaucracy
• Direct impact on mission-critical systems powering global trading
• Compensation designed to attract and retain top 1% engineers

If you are a backend engineer with deep Python, Kubernetes, and distributed systems expertise — and you prefer high-performance, startup-style engineering environments over corporate rigidity — we strongly encourage you to reach out.