NominalIntegrates and configures it
Deployment Systems Engineer
Austin, TX · Los Angeles, CA · +1 moreAustin, TX +2
$120,000–$230,000
Updated
$200,000–$250,000Jersey City, NJHybrid
Own end-to-end deployment and operational stability of Neural Concept's AI design and simulation platform for named enterprise accounts.
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$200K–$250KAbove the median
Median $190K
This job$200K–$250KTypical senior FDE payMiddle 50% of 1,789 postings$160K–$220KIntegrates and configures it
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Posted by Neural Concept on
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.
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.
You will often be the only Neural Concept engineer in the room. We are looking for someone with:
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.
View posting at Neural Concept
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