Site Reliability Engineer

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You will work across software engineering, infrastructure and production operations to improve the reliability, performance and scalability of a global trading platform. This is a development-first reliability role: you will write production-quality automation and tooling, improve observability, streamline deployments and help eliminate classes of operational failure.

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You will collaborate closely with trading-system engineers, quant researchers, infrastructure engineers and platform teams in a fast-moving, low-latency environment.

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• Strong software engineering skills, ideally in Python and/or Go. \n

• Deep Linux expertise, including systems troubleshooting, performance analysis and production operations. \n

• Experience building automation, internal tooling or infrastructure platforms in a production environment. \n

• Solid understanding of CI/CD, Git-based workflows and modern deployment practices. \n

• Experience with Infrastructure as Code, such as Terraform, Ansible or equivalent. \n

• Strong observability experience using tools such as Prometheus, Grafana, ELK/OpenSearch or similar. \n

• Experience supporting distributed, high-availability or performance-sensitive systems. \n

• Strong networking fundamentals, including TCP/IP, latency, throughput and troubleshooting. \n

• Ability to debug issues across the full stack: application, operating system, network, storage and infrastructure. \n

• Excellent communication skills and a collaborative, ownership-driven mindset. \n, * Experience in HFT, proprietary trading, market making, fintech, gaming, telecoms or another low-latency environment. \n

• Exposure to trading systems, market data, exchange connectivity, colocation or real-time data pipelines. \n

• Kubernetes, Docker, EKS or on-premises container platforms. \n

• Cloud experience with AWS, including EC2, S3, networking and managed services. \n

• Experience with Kafka, RabbitMQ or other streaming/message-queue technologies. \n

• Familiarity with C++, Rust or low-level performance profiling. \n

• Experience with time-series databases, ClickHouse, Cassandra or other high-performance data stores. \n

• Experience with configuration management, bare-metal provisioning or data-centre automation. \n

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• Design, build and maintain automation, deployment and configuration tooling for trading and research infrastructure. \n

• Develop internal platforms and services using Python and/or Go. \n

• Build and improve CI/CD pipelines, release workflows, environment management and deployment automation. \n

• Operate and enhance Linux-based production environments across on-premises data centres and cloud infrastructure. \n

• Build observability solutions including metrics, logging, tracing, alerting, dashboards and automated remediation. \n

• Investigate and resolve complex production incidents, performing deep technical root-cause analysis. \n

• Improve system resilience through redundancy, failover design, capacity planning and proactive performance tuning. \n

• Use Infrastructure as Code to provision and manage infrastructure, including Terraform and/or Ansible. \n

• Support containerised workloads and Kubernetes-based platforms where appropriate. \n

• Work with networking, storage and compute teams to optimise low-latency, high-throughput systems. \n

• Participate in an on-call rotation and drive improvements through post-incident reviews and automation. \n

• Partner with engineering teams to establish best practices for reliability, testing, deployment and operational excellence. \n

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Our client is a leading global high-frequency trading firm that designs, builds and operates its trading infrastructure in-house. In an environment where reliability, latency and engineering quality directly affect business performance, technology is treated as a core competitive advantage.