About spectro cloud

spectro 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.

Responsibilities

- translate customer outcomes into deployable architectures and build the required automation and integrations.
- guide deployments from initial capability through production readiness, scaled adoption and operational hand‑off.
- work across paletteai, kubernetes, cloud, bare‑metal, edge, gpu systems, data pipelines, high‑performance networking and the nvidia ecosystem.
- collaborate with other forward deployed engineering (fde) resources and deployment strategists.
- provide hands‑on engineering, not just documentation or demos.
- feed back learnings to product and engineering to improve future deployments.
- communicate architecture trade‑offs, status and risk to engineers, operators, executives and non‑technical stakeholders.
- work onsite with customers for discovery, deployment, testing and operational milestones.

Required Qualifications

- bachelor’s degree in computer science, computer engineering, information systems or equivalent experience.
- at least 6 years of experience in software/platform/devops/site‑reliability engineering or a comparable customer‑facing technical role.
- production experience designing, deploying, upgrading and troubleshooting kubernetes clusters and cloud-native applications.
- strong linux and distributed‑systems fundamentals.
- proficiency in go or python and ability to write production‑quality code.
- hands‑on experience with iac tools such as terraform, ansible, cluster api, helm, kustomize.
- experience implementing ci/cd or gitops workflows (github actions, gitlab ci, jenkins, argo cd, flux).




- knowledge of kubernetes security, multi‑tenancy, rbac, network policies, secrets, etc.
- experience with at least one major public cloud and one datacenter deployment model (bare‑metal, vmware, kubevirt, proxmox, openstack).
- understanding of gpu‑enabled infrastructure, cuda, device plugins and scheduling.
- solid networking fundamentals (tcp/ip, routing, bgp, load balancing, overlays, latency, bandwidth).
- familiarity with high‑performance ai networking concepts (rdma, roce, infiniband, sr‑iov, gpudirect).
- ability to work onsite with customers and satisfy specific access requirements.

Preferred Qualifications

- 8+ years of relevant experience, including ownership of complex production deployments.
- direct experience with spectro cloud palette/paletteai, cluster api, kubernetes fleet management or declarative full‑stack platforms.
- relevant certifications (cka, cks, ckad, cloud, networking, security or nvidia).
- production experience with nvidia cloud partner (ncp) or similar multi‑tenant gpu cloud environments.
- deep experience with tenant isolation across bare‑metal, vms, kubernetes control planes, gpu resources and high‑performance networks.
- hands‑on experience with nvidia gpu operator, network operator, dcgm, mig, vgpu, nim, triton, tensorrt, llm, nccl or nvidia ai enterprise.
- experience with ai platform technologies (run:ai, slurm, volcano, kai, ray, kubeflow, clearml).
- experience with high‑performance storage and ai data platforms (object storage, nvme‑of, parallel file systems, data lakes, feature stores, vector databases, model registries).
- experience in air‑gapped, sovereign, regulated or classified environments.
- contributions to open‑source projects, reference architectures or technical publications.

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📌 Senior forward deployed solution engineer (Italia)
🏢 Spectro Cloud
📍 Italia