Cloud Solutions Architect (US)

Posted 8 Hours Ago
Be an Early Applicant
10 Locations
Remote or Hybrid
200K-250K Annually
Senior level
Artificial Intelligence • Automotive • Information Technology • Software
The Role
Own enterprise customer deployments from architecture through go-live and ongoing operations. Integrate the platform with identity, data, engineering, infrastructure, and model-serving systems across managed Kubernetes, cloud, on-premises, air-gapped, GPU, and HPC environments. Lead security reviews, troubleshoot complex infrastructure issues, support customers, create operational documentation, and feed deployment insights into Product.
Summary Generated by Built In

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.

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.

You Get

  • Work with a world-class technology team – our engineers are top-notch, and we always aim for excellence.

  • Benefit from a competitive salary and rewarding opportunities as we continue to scale.

  • Thrive in a collaborative, multicultural environment where your work is visible and recognized.

  • Develop professionally alongside talented colleagues who share knowledge freely and support one another.

  • Make a global impact by helping customers shift to AI-assisted design, making innovation faster, smarter, and more sustainable.

  • Balance life and work with remote work or hybrid model (20% remote) —we care about results, not rigid schedules.

  • Enjoy paid vacations, healthcare (medical/vision/dental), 401K matching

Where You Will Be

  • Jersey City office or West Coast;

  • Travelling: This position will require travelling to customer locations in the US.

  • Start date: ASAP

  • Eligibility: ITAR clearance required

We're proud to be an equal opportunity employer, and we're committed to building a diverse and inclusive environment where you can thrive.

Skills Required

  • 6+ years deploying and operating enterprise software in production
  • At least 2 years working in customer environments or infrastructure not directly controlled by the employer
  • Configuration-depth experience with Kubernetes, including Helm values, rendered manifests, and workload troubleshooting
  • Knowledge of identity and SSO fundamentals, including OIDC, SAML, credential rotation, redirect URIs, and group-to-role mapping
  • Experience with Linux, networking, DNS, routing, ingress, egress, TLS, certificate chains, and interception proxies
  • Experience with Kubernetes storage, persistent volumes, CSI, access modes, and shared-storage troubleshooting
  • Personally carried and supported a production deployment
  • Professional customer-facing English communication skills
  • Willingness to travel to customer locations and work customer hours
  • ITAR clearance eligibility or authorization
  • Experience with regulated or air-gapped deployments
  • Experience with private registries, image mirroring, GPU scheduling, or LLM serving
  • Enterprise identity provider administration
  • Terraform and GitOps
  • Prometheus and Grafana
  • HPC schedulers, ISO 27001 evidence, and Python
  • PLM, CAD, or CAE industry exposure
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The Company
HQ: Lausanne
91 Employees
Year Founded: 2018

What We Do

Neural Concept is revolutionizing engineering with AI. We provide a leading end-to-end platform that places AI at the center of the product development process, helping engineers design faster, smarter, and better. Our Engineering Intelligence platform empowers teams to build and deploy AI-driven workflows that drastically shorten development cycles, boost design quality, and increase competitiveness — all while embedding the team’s know-how into the tools they use every day. Spun out from EPFL in 2018, Neural Concept works with over 70% of the world’s largest OEMs and 40 of the top 100 Tier-1 suppliers. Neural Concept is backed by Forestay Capital and the D.E. Shaw group.

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