Senior forward deployed solution engineer
h3About spectro cloud /h3pspectro cloud helps enterprises, sovereign ai clouds and public sector organisations build, govern and operate ai infrastructure in any environment, from edge to cloud and from metal to token factory. /ph3Responsibilities /h3ullitranslate customer outcomes into deployable architectures and build the required automation and integrations. /liliguide deployments from initial capability through production readiness, scaled adoption and operational hand‑off. /liliwork across paletteai, kubernetes, cloud, bare‑metal, edge, gpu systems, data pipelines, high‑performance networking and the nvidia ecosystem. /lilicollaborate with other forward deployed engineering (fde) resources and deployment strategists. /liliprovide hands‑on engineering, not just documentation or demos. /lilifeed back learnings to product and engineering to improve future deployments. /lilicommunicate architecture trade‑offs, status and risk to engineers, operators, executives and non‑technical stakeholders. /liliwork onsite with customers for discovery, deployment, testing and operational milestones. /li /ulh3Required Qualifications /h3ullibachelor’s degree in computer science, computer engineering, information systems or equivalent experience. /liliat least 6 years of experience in software/platform/devops/site‑reliability engineering or a comparable customer‑facing technical role. /liliproduction experience designing, deploying, upgrading and troubleshooting kubernetes clusters and cloud-native applications. /lilistrong linux and distributed‑systems fundamentals. /liliproficiency in go or python and ability to write production‑quality code. /lilihands‑on experience with iac tools such as terraform, ansible, cluster api, helm, kustomize. /liliexperience implementing ci/cd or gitops workflows (github actions, gitlab ci, jenkins, argo cd, flux).
/liliknowledge of kubernetes security, multi‑tenancy, rbac, network policies, secrets, etc. /liliexperience with at least one major public cloud and one datacenter deployment model (bare‑metal, vmware, kubevirt, proxmox, openstack). /liliunderstanding of gpu‑enabled infrastructure, cuda, device plugins and scheduling. /lilisolid networking fundamentals (tcp/ip, routing, bgp, load balancing, overlays, latency, bandwidth). /lilifamiliarity with high‑performance ai networking concepts (rdma, roce, infiniband, sr‑iov, gpudirect). /liliability to work onsite with customers and satisfy specific access requirements. /li /ulh3Preferred Qualifications /h3ulli8+ years of relevant experience, including ownership of complex production deployments. /lilidirect experience with spectro cloud palette/paletteai, cluster api, kubernetes fleet management or declarative full‑stack platforms. /lilirelevant certifications (cka, cks, ckad, cloud, networking, security or nvidia). /liliproduction experience with nvidia cloud partner (ncp) or similar multi‑tenant gpu cloud environments. /lilideep experience with tenant isolation across bare‑metal, vms, kubernetes control planes, gpu resources and high‑performance networks. /lilihands‑on experience with nvidia gpu operator, network operator, dcgm, mig, vgpu, nim, triton, tensorrt, llm, nccl or nvidia ai enterprise. /liliexperience with ai platform technologies (run:ai, slurm, volcano, kai, ray, kubeflow, clearml). /liliexperience with high‑performance storage and ai data platforms (object storage, nvme‑of, parallel file systems, data lakes, feature stores, vector databases, model registries). /liliexperience in air‑gapped, sovereign, regulated or classified environments. /lilicontributions to open‑source projects, reference architectures or technical publications. /li /ul #J-18808-Ljbffr
/liliknowledge of kubernetes security, multi‑tenancy, rbac, network policies, secrets, etc. /liliexperience with at least one major public cloud and one datacenter deployment model (bare‑metal, vmware, kubevirt, proxmox, openstack). /liliunderstanding of gpu‑enabled infrastructure, cuda, device plugins and scheduling. /lilisolid networking fundamentals (tcp/ip, routing, bgp, load balancing, overlays, latency, bandwidth). /lilifamiliarity with high‑performance ai networking concepts (rdma, roce, infiniband, sr‑iov, gpudirect). /liliability to work onsite with customers and satisfy specific access requirements. /li /ulh3Preferred Qualifications /h3ulli8+ years of relevant experience, including ownership of complex production deployments. /lilidirect experience with spectro cloud palette/paletteai, cluster api, kubernetes fleet management or declarative full‑stack platforms. /lilirelevant certifications (cka, cks, ckad, cloud, networking, security or nvidia). /liliproduction experience with nvidia cloud partner (ncp) or similar multi‑tenant gpu cloud environments. /lilideep experience with tenant isolation across bare‑metal, vms, kubernetes control planes, gpu resources and high‑performance networks. /lilihands‑on experience with nvidia gpu operator, network operator, dcgm, mig, vgpu, nim, triton, tensorrt, llm, nccl or nvidia ai enterprise. /liliexperience with ai platform technologies (run:ai, slurm, volcano, kai, ray, kubeflow, clearml). /liliexperience with high‑performance storage and ai data platforms (object storage, nvme‑of, parallel file systems, data lakes, feature stores, vector databases, model registries). /liliexperience in air‑gapped, sovereign, regulated or classified environments. /lilicontributions to open‑source projects, reference architectures or technical publications. /li /ul #J-18808-Ljbffr