Cloud Solutions Architect (US)

About the role

Neural Concept embeds AI into design and simulation workflows so engineering teams make continuous, data-driven decisions instead of waiting on sequential design–simulation–validation cycles. None of that matters until the platform is running inside the customer's environment, on their infrastructure, under their rules. That is this role. You take an enterprise customer and make the platform real for them: architected, deployed, integrated, cleared by their security organisation, and stable enough that their engineers stop thinking about it. You own that outcome end to end for named accounts, as their primary technical counterpart. This position is based in the Jersey City office or West Coast, requires travel to customer locations in the US, start date ASAP, and requires ITAR clearance.

Responsibilities

• Own the deployment from the first architecture conversation through go-live and into steady‑state operation.
• Integrate the platform with the customer's identity, data and engineering systems, and the underlying infrastructure and model‑serving layer.
• Build relationships with the customer's IT, security and platform teams: conduct assessments, architecture reviews, and be the point of contact when something breaks.
• Diagnose failures, including when the root cause lies outside Neural Concept’s software.
• Create runbooks, post‑mortems and playbooks that streamline future deployments and feed lessons back into Product.

Requirements

• 6+ years deploying and operating enterprise software in production, with at least 2 years in environments you did not control.
• Deep Kubernetes knowledge: how chart values become rendered manifests and why a workload may fail to start.
• Identity and SSO fundamentals: OIDC and SAML, clients, credential rotation, redirect URIs, group‑to‑role mapping.
• Linux, networking and TLS: DNS, routing, ingress/egress, certificate chains and interception proxies.
• Kubernetes storage: persistent volumes, CSI, access modes, diagnosing shared storage that degrades under load.
• A proven production deployment you personally carried out and then supported – be ready to name it, date it, and describe what went wrong.
• Professional customer‑facing English and willingness to travel and work customers’ hours.

Skills

• Experience with 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.
• Exposure to PLM, CAD or CAE tools.

Benefits

• Work with a world‑class technology team focused on excellence.
• Competitive salary and rewarding opportunities as we scale.
• Collaborative, multicultural environment where your work is visible and recognized.
• Professional development alongside talented colleagues who share knowledge freely.
• Global impact by helping customers shift to AI‑assisted design, making innovation faster, smarter, and more sustainable.