Top Infrastructure Engineer Jobs in London

Build and operate resilient, highly available infrastructure for WRITER’s enterprise generative AI platform. Responsibilities include SRE, DevOps, platform engineering, cloud infrastructure, Kubernetes, Terraform, automation, reliability engineering, incident response, SLOs, observability, cost optimization, and root-cause analysis. The role owns systems end to end, leads infrastructure initiatives, improves on-call operations, and collaborates with product, security, and engineering teams in a hybrid London or New York environment.

Deploys, integrates, maintains, and develops AI training factory components in isolated environments. Responsibilities include integrating tooling onto hardware, managing software updates and configuration across environments, ensuring platform reliability, coordinating with autonomy teams, troubleshooting distributed systems, and developing automation. The role requires cloud, Kubernetes, Linux networking, C++ or Python application support, and onsite availability in London.

Build and operate highly available GCP infrastructure for international engineering teams and customer deployments. Manage Kubernetes clusters, automate deployments, develop internal infrastructure tooling, and oversee monitoring, alerting, maintenance, and incident response. Establish async handoffs for continuous global coverage across EU, US, and APAC teams. The role also supports agentic AI and LLM workflows, with opportunities to work on data pipelines and stream-processing architectures.

Design, provision, and operate reliable shared infrastructure across AWS, GCP, Azure, and on-premises environments. Manage Kubernetes clusters, multi-tenancy, secrets, GPU workloads, networking, service meshes, and infrastructure as code using Terraform and Crossplane. Develop operators, establish reliability targets, respond to incidents, and partner with security and platform teams on governance and compliance.

Build and operate production software, APIs, tooling, and automation for large-scale GPU, bare-metal, and HPC infrastructure. Responsibilities include provisioning, configuration, monitoring, lifecycle management, observability, hardware integration, reliability improvements, and infrastructure capacity deployment. The role partners with networking, data center, platform, and infrastructure teams to design scalable systems and define technical direction.

Operate and scale large GPU infrastructure platforms, including Linux systems, bare-metal environments, provisioning workflows, observability, and reliability automation. Responsibilities include platform deployment, incident response, break/fix operations, customer provisioning, on-call participation, infrastructure troubleshooting, and collaboration across engineering, networking, customer success, and software teams. The role also develops automation to reduce manual work and improve operational efficiency.

Designs, deploys, optimizes, and troubleshoots cloud infrastructure for Thought Machine Vault implementations. The role partners directly with client engineering teams across the full project lifecycle, covering infrastructure preparation, high availability, disaster recovery, monitoring, security, deployment, and production support. It also contributes to presales consulting, client feedback, product improvements, and collaboration with internal engineering, SRE, architecture, and commercial teams. Travel to client sites may reach 25% of working time.

Software Engineering Interns will help design, maintain, and scale infrastructure supporting Talos’s digital asset trading and settlement platform. Responsibilities include contributing to CI/CD, infrastructure-as-code, deployment tooling, monitoring, logging, observability, and production performance improvements. Interns will collaborate with engineering teams to implement infrastructure requirements and gain exposure to distributed systems, cloud platforms, Linux, networking, and platform engineering during a 12-week summer internship.

Operate and evolve foundational infrastructure services including Terraform Enterprise, Active Directory, Jenkins and self-hosted platforms. Automate provisioning and lifecycle management, ensure monitoring, backups and recoverability, collaborate with platform and application teams, and participate in on-call incident response and continuous improvement.

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.

Support IT operations across multiple datacenters, focusing on hardware and firmware troubleshooting, process improvement, and collaboration with R&D. Travel for hardware projects is required.

Build, operate, and improve multi-region compute, virtualization, storage, networking, and Kubernetes platforms. Administer VMware vSphere, NSX, and Ceph; develop Ansible and Terraform infrastructure automation; monitor systems with Prometheus and Grafana; support hardware lifecycle operations and incident response. The role also contributes to migrating from VMware to an open-source virtualization platform, documents procedures, collaborates with network engineering, and participates in on-call support.

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.

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.

The role involves owning and improving the design, deployment, and operation of OpenStack and Kubernetes environments, ensuring performance, scalability, and security of GPU workloads, while collaborating cross-functionally and driving automation using infrastructure-as-code practices.

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.

The Azure Architect will design and implement Azure cloud solutions, guide clients in adoption, and lead architecture decisions ensuring security and scalability.

The Staff Infrastructure Security Engineer will lead security initiatives, set architectural patterns, conduct security reviews, and mentor engineers while ensuring security in cloud infrastructures for GitLab.