Top Infrastructure Engineer Jobs in London

Design, operate, secure, and optimize cloud infrastructure across AWS and Azure. Implement IAM, IaC, automation, monitoring, cost controls, and compliance practices. Partner with Security, Engineering, and IT Operations on migrations, incident response, and operational improvements while mentoring junior engineers.

Responsible for operating and maintaining edge infrastructure, managing cloud and physical servers, troubleshooting systems, and automating tasks while collaborating with multiple teams.

The role involves maintaining and optimizing Palantir software systems, developing automated workflows, and collaborating on infrastructure challenges for government solutions.

Lead design, delivery and maintenance of on-prem and cloud market-data distribution systems (real-time, historical, AI/ML use cases). Collaborate with product/stakeholders, provide 3rd-level operational support, validate AI-assisted recommendations, ensure resiliency, security, auditability and strong process controls.

Lead infrastructure engineering for critical market data platforms: provide production support, implement changes, lead architecture and automation workstreams, validate AI-assisted recommendations, ensure performance, resilience and data quality, and collaborate across platforms to modernize and stabilize trading market data infrastructure.

Design, deploy, and maintain tools and services for build, CI/CD, packaging, and releases. Manage cloud and Kubernetes infrastructure, use IaC, reduce toil, and support junior engineers for reliable ML software delivery.

Lead infrastructure engineering for proxy and secure web gateway solutions: manage stakeholders, troubleshoot proxy issues, deploy and automate proxy security systems, improve runbooks/change processes, mentor engineers, and align solutions with organizational goals.

The Senior Backend Software Engineer collaborates in teams to design and build scalable infrastructure systems, optimizing data-driven applications across sectors.

Backend Software Engineers at Palantir build scalable software solutions, collaborate across teams, and develop systems for data processing and storage, enhancing product capabilities.

Designs, implements, secures, and maintains global network and infrastructure environments across international offices. Responsibilities include Azure networking, Check Point SASE, Aruba switching and wireless, Windows Server, Hyper-V, Active Directory, Veeam backups, monitoring, patching, vulnerability remediation, troubleshooting, project delivery, and external vendor coordination. Provides second- and third-level support while contributing to infrastructure modernization and operational stability.

Infrastructure Engineers will join a newly formed infrastructure engineering team. Responsibilities require production experience with AWS or configuration management tools, scripting in Go, PHP, Bash, or Python, and running Docker in production.

Design, build, migrate, operate and govern hybrid cloud and on-prem infrastructure. Architect and deliver cloud transformations, implement virtualization, container platforms, automation, and resilience strategies.

As a Senior Infrastructure Engineer, you'll design and build infrastructure solutions, manage cloud services, enhance CI/CD pipelines, and automate operations. You'll lead system architecture while ensuring security, reliability, and performance in collaboration with product engineers.

Build and maintain scalable ML infrastructure for LLM post-training, RL, evaluation, inference, and agentic workflows. Design data-control systems, optimize training and inference performance across networking, storage, and compute, and deliver tooling for experiments, evals, dashboards, reproducibility, and failure inspection. Collaborate with researchers and product to iterate models and infrastructure.

The AI Infrastructure Engineer will build and optimize training pipelines and inference services for AI models, enhance GPU-level performance, and mentor team members.

The Staff Infrastructure Engineer will lead the strategy for agent-driven cluster lifecycle management, ensuring secure and scalable compute systems while mentoring junior engineers.

The Senior ML Infrastructure Engineer will manage and optimize the ML infrastructure, focusing on training pipelines, model serving, and collaboration with research teams.

Design, develop, and operate Pigment’s production SaaS platform, with a focus on backend infrastructure. Translate functional requirements into elegant software, contribute throughout the application lifecycle, and improve infrastructure using Kubernetes, infrastructure-as-code tooling, and public cloud technologies. Collaborate closely with engineering teams and understand customer needs to deliver reliable, scalable product capabilities.

Own and operate the internal platform for engineering: design and run Kubernetes and bare-metal infrastructure, automate via Terraform/Ansible and scripting, build CI/CD and self-service tooling, optimise networking and storage for ML/hardware workloads, implement monitoring and security (IAM, secrets, threat detection), and drive reliability and continuous improvement.

Build and operate Kubernetes-based infrastructure and tooling to support development, testing, deployment and scaling of Graphcores ML software. Manage cloud infrastructure, CI/CD practices, and collaborate with software teams to improve reliability and observability of HPC AI platforms.

Leads UK-hosted cloud infrastructure design and deployment across cloud, on-premise, air-gapped, and secure environments. Builds infrastructure as code, manages Kubernetes and CI/CD systems, hosts approved AI models, improves developer tooling, supports Hardware in the Loop integration, and troubleshoots distributed systems. Partners with product managers, customers, and global infrastructure teams to deliver secure technical solutions for defense and national security programs.

Design, build, and maintain scalable, fault-tolerant serving platforms for LLMs. Integrate models for production and research, implement monitoring and observability, perform architecture reviews, and lead cross-functional end-to-end projects enabling LLM capability discovery and high-performance serving.

Design, operate, and scale large distributed systems for telemetry processing. Build automation, use AI tooling to reduce toil, ensure availability and disaster recovery, participate in on-call incident response, troubleshoot production AWS/Kubernetes environments, and collaborate with application teams to meet SLOs/SLAs.

Lead and implement core infrastructure platform initiatives (multi-account/region Kubernetes clusters, MLOps, standardized deployments, authentication). Collaborate with product engineering stakeholders to scope requests, remove operational toil via automation, drive platform adoption, and mentor engineers to improve developer productivity across the organization.

Lead the development of AI/ML infrastructure for simulations using large foundation models. Collaborate on realistic simulation improvements and mentor junior engineers.