DevOps / Platform Engineer

Qube Research & Technologies (QRT) is a global quantitative and systematic investment manager, operating in all liquid asset classes across the world. We are a technology and data-driven group implementing a scientific approach to investing. Combining data, research, technology, and trading expertise has shaped QRT’s collaborative mindset, which enables us to solve the most complex challenges. QRT’s culture of innovation continuously drives our ambition to deliver high-quality returns for our investors. As a DevOps / Platform Engineer, you will build and operate the infrastructure that powers QRT's internal AI platform. You will be responsible for the Kubernetes and AWS environments supporting model serving, observability, and developer tooling, ensuring they remain reliable, secure, and scalable. Working closely with AI Platform Engineers, Researchers, and Data Scientists, you will own core infrastructure services and help shape how AI capabilities are delivered across the firm. Your future role within QRT: Infrastructure & Cloud Design and operate infrastructure across AWS and on-premise Kubernetes environments supporting AI and LLM workloads Manage Kubernetes clusters, including scheduling, multi-tenancy, resource isolation, and GPU-backed workloads Develop hybrid cloud strategies balancing performance, cost, and data residency requirements Own AWS infrastructure, including networking, IAM, security, and cost management Build and maintain infrastructure as code using reusable, version-controlled tooling Platform Operations Implement and maintain CI/CD and GitOps deployment workflows Build observability solutions covering system health, utilisation, latency, and platform performance Automate scaling and capacity management Enforce authentication, rate limiting, auditability, and cost attribution across platform services Define and operate against infrastructure SLOs Collaboration Partner with AI Platform Engineers to support model serving and inference workloads Enable internal teams through platform tooling, onboarding, and self-service capabilities Your present skillset: 4+ years of experience in Cloud, DevOps, or Platform Engineering Strong Kubernetes expertise, including cluster operations, multi-tenancy, GPU scheduling, and Helm/Kustomize Hands-on AWS experience covering networking, IAM, EKS, EC2, and cost management Strong Python skills and experience with infrastructure-as-code tools such as Terraform Experience building and operating CI/CD and GitOps workflows Experience defining and managing infrastructure SLOs Pragmatic, ownership-driven approach with the ability to work effectively in ambiguous environments Nice to Have Experience supporting LLM inference workloads, model serving platforms, or GPU-backed infrastructure Familiarity with RAG systems, vector databases, or AI-related data platforms Experience building internal APIs or platform services Understanding of agentic AI architectures and platform requirements Background in high-performance or latency-sensitive environments AWS or Kubernetes certifications (CKA, CKAD, Solutions Architect, etc.) QRT is an equal opportunity employer. We welcome diversity as essential to our success. QRT empowers employees to work openly and respectfully to achieve collective success. In addition to professional achievement, we are offering initiatives and programs to enable employees achieve a healthy work-life balance.