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Kubernetes Engineer

  • Infrastructure Engineering
  • London

We tackle the most complex problems in quantitative finance, by bringing scientific clarity to financial complexity.

From our London HQ, we unite world-class researchers and engineers in an environment that values deep exploration and methodical execution - because the best ideas take time to evolve.  Together we’re building a world-class platform to amplify our teams’ most powerful ideas.

As part of our engineering team, you’ll shape the platforms and tools that drive high-impact research - designing systems that scale, accelerate discovery and support innovation across the firm.

Take the next step in your career.

The role

We are seeking a highly skilled and motivated Kubernetes Engineer to join our world-class engineering team. In this role, you’ll play a pivotal part in shaping the platforms that enable our research teams to run cutting-edge workloads at scale. You will be responsible for designing, building and operating mature Kubernetes-based infrastructure that is secure, resilient and highly automated, ensuring it can support a wide range of demanding compute requirements. 

Our environment spans everything from GPU-intensive machine learning model training to ultra-low latency workloads, requiring meticulous attention to performance, reliability and scalability. You’ll work closely with researchers and engineers  to deliver platforms that not only meet immediate needs but also anticipate future growth and innovation. 

Key responsibilities of the role include:

  • Designing and operating custom Kubernetes operators and controllers to automate infrastructure beyond off-the-shelf solutions

  • Guaranteeing multi-tenant security and isolation, enforcing RBAC and policies with OPA/Gatekeeper 

  • Engineering GitOps-driven CI/CD pipelines (ArgoCD, FluxCD) for safe, auditable changes

  • Driving Infrastructure as Code practices with Terraform and Helm for reliable and repeatable builds

  • Heavily embedding observability using Prometheus, Grafana and OpenTelemetry to make systems measurable and reliable

  • Staying ahead of Kubernetes evolution, testing and adopting new versions and features early

  • Collaborating with teams across the business, refining requirements, challenging assumptions and prioritising developer experience

  • Contributing to an on-call rotation, taking ownership of incidents, solving problems openly and sharing responsibility in a no blame culture

  • Capturing and sharing knowledge, writing clear runbooks and postmortems, and designing documentation

Who are we looking for?

The ideal candidate will have the following skills and experience: 

  • Strong Linux system engineering background 

  • Strong programming ability in Go or Python, ideally with experience building Kubernetes operators or controllers 

  • Strong understanding of Kubernetes internals, including CRDs, RBAC, custom controllers and scheduler extensions 

  • Hands-on experience with Helm and GitOps workflows 

  • Experience implementing multi-tenant security controls in Kubernetes, including namespace isolation, network policies and Open Policy Agent

  • Proven ability to troubleshoot complex performance and reliability issues across infrastructure and workloads 

  • Experience with observability tools such as Prometheus, Grafana and OpenTelemetry to monitor cluster metrics and health 

  • Strong communication skills, with experience collaborating with internal platform users to gather feedback and deliver improvements 

  • Experience writing and maintaining technical documentation, runbooks and post-incident reviews 

The following skills and experience is desirable:

Experience with Cilium or other CNI plugin 

  • Experience with platforms such as OpenStack or VMware 

  • Experience with Amazon Web Services EKS  

  • Experience working with GPU-intensive workloads, such as large language models, ML training pipelines or scientific computing 

  • Experience with KubeVirt 

  • Contributions to open-source projects within the Kubernetes ecosystem 

  • Familiarity with container runtimes such as CRI-O, containerd and the NVIDIA Container Toolkit 

  • Familiarity with NVIDIA tooling for containers 

  • Understanding of SLOs, SLAs and error budgets 

We value engineers who bring curiosity, pragmatism and collaboration to their work who are motivated to grow continuously while helping those around them do the same. 

Why should you apply?

  • Highly competitive compensation plus annual discretionary bonus
  • Lunch provided (via Just Eat for Business) and dedicated barista bar
  • 30 days’ annual leave
  • 9% company pension contributions
  • Informal dress code and excellent work/life balance
  • Comprehensive healthcare and life assurance
  • Cycle-to-work scheme
  • Monthly company events
Location: London
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Yousuf Machine Learning Engineer

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Interview process

Online Application

Our assessment process kicks off with our Talent Acquisition team, who will review your application and assess your fit for the role.

Stage One: Technical Interview

You will meet with a team member – or take a remote test – where your technical abilities will be put to the test.

Stage Two: Behavioural Interview

We will set aside technical skills and focus on you.

Stage Three: Further Technical Interviews

Here, we will take a deeper dive into your technical skills and competencies.

Stage Four: Management Interviews

The final stage of our interview process is where you will meet members of your team, your future manager, and functional leadership.

Kubernetes Engineer Apply now

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