Cloud Solutions Architect

What you will do

• The deployment, from the first architecture conversation through go-live and into steady-state operation.
• Its integration with the customer's identity, data and engineering systems, and the infrastructure and model serving layer beneath it.
• The relationship with their IT, security and platform teams: assessments, architecture reviews, and the call when something breaks.
• The diagnosis when it does break, including when the cause sits outside our own software.
• The runbooks, post-mortems and playbooks that make the next deployment easier, and the feedback loop into Product.
• Where you will do it Managed Kubernetes across the major clouds. On-premises and fully air-gapped clusters with no route to the internet, GPU infrastructure, self-hosted model serving. Customer HPC environments, schedulers, and shared storage under real load.
• If installing software with no internet access, on hardware you do not control, reads as the interesting part of the job rather than the obstacle, this will suit you.
• Who you are
• You will often be the only Neural Concept engineer in the room. We are looking for someone with:
• 6+ years deploying and operating enterprise software in production, two of them in environments you did not control.
• Kubernetes at configuration depth: how chart values become rendered manifests, and why a workload will not start.
• Identity and SSO fundamentals: OIDC and SAML, clients and credential rotation, redirect URIs, group-to-role mapping.
• Linux, networking and TLS: DNS, routing, ingress and egress, certificate chains and interception proxies.
• Kubernetes storage: persistent volumes and CSI, access modes, diagnosing shared storage that degrades under load.
• A production deployment you personally carried and then supported. Name it, date it, tell us what went wrong.
• Professional customer-facing English, and willingness to travel and work your customers' hours.
• Also valuable: regulated or air-gapped deployments · private registries and image mirroring · GPU scheduling and LLM serving · enterprise IdP administration · Terraform and GitOps · Prometheus and Grafana · HPC schedulers · ISO 27001 evidence · Python · PLM, CAD or CAE exposure.