About the job

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.

Where You Will Be

Remote from Europe or one of our offices in Switzerland or Munich;
Travelling: This position will require travelling to customer location within Europe
Start date: ASAP

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

Responsibilities