Radiant ir mākslīgā intelekta infrastruktūras nodrošinātājs, kas apkalpo uzņēmumus un citas organizācijas, kuras izmanto liela mēroga mākslīgā intelekta darba slodzes. Tās FlightDeck platforma nodrošina pārredzamību un darbības pārvaldību, savukārt infrastruktūras portfelī ietilpst bare metal un virtuālo mašīnu skaitļošanas resursi, GPU, pārvaldīts Kubernetes, Slurm, krātuves, tīkli un datu centru jaudas. Radiant izstrādā arī suverēnus un hipermēroga risinājumus komandām, kurām nepieciešamas drošas, pārvaldītas un mērogojamas mākslīgā intelekta vides. Uzņēmums pieņem darbā darbiniekus infrastruktūras, mākslīgā intelekta un uzņēmumu tehnoloģiju jomās.
Senior Infrastructure Engineer, AI Cloud Platform
Design and operate Radiant’s AI-native cloud platform, building infrastructure across Kubernetes, HPC, bare metal, networking, storage, security, and automation.
Apraksts
- Architect and implement Radiant’s next-generation AI-native cloud platform.
- Operate virtualization for AI workloads, including hypervisor tuning for HPC environments.
- Scale compute, storage, and networking capacity to meet customer demand.
- Build provisioning, orchestration, and lifecycle management for bare-metal hardware.
- Maintain secure, high-performance Unix and Linux configurations at scale.
- Deliver high-performance cloud-native storage and networking.
- Manage Kubernetes clusters across hybrid and multicloud environments using CNIs and service meshes.
- Build and maintain CI/CD pipelines for automated infrastructure delivery.
- Secure Kubernetes with RBAC, network policies, admission controllers, and related tools.
- Manage and rotate secrets across clusters.
- Protect the software supply chain through image scanning, signed artifacts, and provenance attestations.
- Enforce least-privilege IAM across bare-metal systems, clusters, and cloud control planes.
- Develop observability pipelines for logs, metrics, and traces.
- Create infrastructure automation with Terraform, Ansible, Go, and Python.
- Evaluate emerging technologies and determine their fit for the platform.
- Develop low-level designs and implementation plans.
- Partner with cross-functional teams and contribute to design reviews.
- Write technical documentation and operational runbooks.
- Support junior engineers through pairing, code reviews, and design feedback.
- Coordinate across teams to deliver infrastructure projects end to end.
Prasības
- Hands-on experience delivering infrastructure at scale in cloud-native, HPC, or AI-native environments.
- A track record of assessing and adopting tools and technologies.
- Extensive experience with large-scale global infrastructure, particularly AI-native, HPC, and cloud-native systems.
- Strong Kubernetes fundamentals, including container networking (CNI) and service mesh technologies.
- In-depth knowledge of virtualization and hypervisors for high-performance workloads.
- Strong command of TCP, UDP, DNS, BGP, and software-defined networking.
- Proficiency with infrastructure-as-code tools such as Terraform and Ansible.
- Practical coding experience with Go, Python, or similar languages for automation.
- Working knowledge of Prometheus, Grafana, and distributed tracing systems.
- Strong communication and collaboration skills.
- Ability to explain complex technical concepts to cross-functional teams.
- Ability to write clear, concise infrastructure documentation.
- Preferred: experience with AI/ML workloads, GPU-accelerated systems, HPC, GPU partitioning with MIG, NVIDIA GPU Operator, RDMA, InfiniBand, RoCEv2, GPUDirect, Ceph, parallel filesystems, hybrid cloud, edge computing, or architecture leadership.
Priekšrocības
- Contribute to a rapidly growing AI infrastructure business at the industry's forefront.
- Work across a broad, advanced stack spanning physical and software infrastructure.
- Develop your career at a Brookfield-backed company.
- Access resources, mentorship, and opportunities for professional growth.
- Contribute directly to business decisions.