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ai-инструменты
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описание
Location: UK (occasional office travel) | Employment Type: Full-time, Permanent | Reports to: Engineering Manager
We’re looking for a Principal Infrastructure Engineer in our Platform team to drive the architecture, design, and implementation of our next-generation AI-native cloud platform. You will analyse cutting-edge technologies, design scalable and resilient infrastructure solutions, and lead their implementation across a globally distributed environment. You’ll combine deep technical expertise with solution-focused leadership, you will enable our infrastructure to power HPC and AI/ML workloads, delivering value through innovation and collaboration.
задачи
Infrastructure Design & Virtualisation:
Architect, design and implement virtualisation solutions optimised for AI-native workloads, focusing on HPC environments and hypervisor tuning.
Design infrastructure that dynamically adjusts to meet customer demands for storage and networking resources, ensuring resilience and scalability.
Bare-Metal and Operating System Management:
Lead the lifecycle management of bare-metal hardware, ensuring efficient provisioning, orchestration, and optimisation.
Maintain deep expertise in Unix/Linux systems, delivering secure, performant configurations at scale.
Networking and High-Performance Storage:
Design and implement high-performance, cloud-native storage and networking solutions for demanding workloads.
Apply advanced knowledge of networking protocols (TCP, UDP, DNS, encryption) and software-defined networking (SDN) technologies.
Kubernetes and Cloud-Native Platforms:
Deploy and manage Kubernetes clusters across hybrid and multi-cloud environments, leveraging CNIs and service meshes.
Architect scalable CI/CD pipelines to automate infrastructure delivery and ensure reliable global operations.
IAM and least-privilege design across bare-metal, cluster, and cloud control planes
Observability and Automation:
Build observability pipelines to monitor and troubleshoot global systems, integrating tools for logs,metrics, and tracing.
Create automation frameworks to reduce operational toil, streamline deployments, and enhance scalability using tools like Terraform, Ansible, Go, and Python.
Architecture & Solution Design:
Analyse emerging technologies and assess their potential fit within our platform, considering scalability, security, and performance.
Develop high- and low-level architectural proposals, balancing technical and business requirements.
Collaborate with cross-functional teams to ensure successful implementation of infrastructure solutions.
Provide thought leadership on architecture best practices, driving alignment across engineering and product teams.
Collaboration and Leadership:
Foster a 'how do we achieve this?' mindset, championing a positive, solution-oriented approach to challenges.
Mentor and guide team members in architectural principles, emerging technologies, and best practices.
Partner with engineering leaders and stakeholders to align infrastructure projects with broader organisational goals.
требования
Proven experience in infrastructure architecture and solution design, including the ability to produce detailed technical proposals.
Demonstrated success in evaluating and adopting new toolsets and technologies.
Extensive expertise in large-scale global infrastructure deployments, particularly in AI-native, HPC, and cloud-native environments.
Advanced knowledge of Kubernetes fundamentals, container networking (CNI), and service mesh technologies.
Deep understanding of virtualisation and hypervisor technologies for high-performance workloads.
Strong proficiency in networking protocols (TCP, UDP, DNS, BGP) and SDN solutions.
Skilled in Infrastructure-as-Code (IaC) tools like Terraform, Ansible, and cloud orchestration frameworks.
Hands-on coding experience in Go, Python, or similar languages for automation.
Solid grasp of observability tools (Prometheus, Grafana) and distributed tracing systems.
Strong communication and collaboration skills, with the ability to convey complex technical concepts to cross-functional teams.
Demonstrate ability to create clear and concise documentation for infrastructure designs, processes and systems.
Expertise in AI/ML workloads, GPU-accelerated systems, or HPC infrastructures, including GPU partitioning with MIG and the NVIDIA GPU Operator.
Experience with RDMA fabrics such as InfiniBand or RoCEv2, and GPUDirect data paths.
High-throughput distributed storage at scale, such as Ceph or a parallel filesystem.
Familiarity with hybrid cloud and edge computing principles.
Experience leading architecture initiatives in agile environments, working iteratively to deliver high-quality results.
условия
Work on a rapidly scaling AI infrastructure business at the forefront of the industry
Get broad exposure to a cutting-edge physical & software infrastructure stack
Be part of a team where you're genuinely valued and your work directly enables business decisions
Develop your career in a Brookfield-backed company with resources, mentorship, and genuine growth opportunities
