Platform Deployment Engineer - West Coast

Neural Concept; United States; Hybrid; USD 140,000 - 200,000; Full time

Benefits offered by this job

Hybrid work arrangement (20% remote)

Medical, vision and dental coverage

401(k) matching

Paid vacation

Job summary

Neural Concept is seeking a seasoned Deployment Engineer to own enterprise AI platform deployments from architecture through production support. You will be the primary technical contact, ensuring seamless integration with customer systems and guiding engineering teams on applying AI to complex design and simulation processes.

Responsibilities include leading deployment projects end-to-end, integrating with customer IT/security, and troubleshooting across environments including on-prem and

Qualifications

• Six+ years of production enterprise software deployment and operations experience, including two years in externally controlled environments.
• Strong Kubernetes configuration and debugging skills (charts, rendered manifests, workload startup).
• Understanding of OIDC and SAML, client configuration, credential rotation, redirect URIs, and group-to-role mappings.
• Experience with Linux, networking, TLS, DNS, routing, ingress and egress, certificate chains, and Kubernetes storage.
• A production deployment you personally delivered and supported, plus professional customer-facing English.
• Willingness to travel to US customer locations and work customer schedules; ITAR clearance is required.
• Nice to have: Terraform, GitOps, Prometheus, Grafana.
• Nice to have: ISO 27001 evidence, Python, HPC schedulers, PLM/CAD/CAE systems.

Responsibilities

• Lead deployment projects through architecture, implementation, go-live, and steady-state operation.
• Integrate with customer identity, data, and engineering systems, as well as infrastructure and model-serving components.
• Partner with customer IT, security, and platform teams during assessments, reviews, and incident response.
• Troubleshoot issues across the deployed environment, including infrastructure and systems outside the platform.
• Write runbooks and post-mortems, improve repeatable deployment guidance, and feed customer learnings back to product teams.
• Operate across managed Kubernetes, on-premises and air-gapped clusters, GPU infrastructure, self-hosted models, and HPC environments.

Skills

Kubernetes config and debugging

Linux networking and TLS

OIDC/SAML familiarity

Customer-facing communication

Travel readiness

ITAR clearance

Tools

Kubernetes

Terraform

GitOps

Prometheus

Grafana

TLS/DNS networking

Job description

Role overview

Take ownership of technical deployments of an enterprise AI platform for customers, from early architecture planning through production launch and ongoing support. As the primary technical contact for assigned accounts, you’ll make the platform work within customer-controlled systems and help engineering teams apply AI to design and simulation processes.

Responsibilities

• Lead deployment projects through architecture, implementation, go-live, and steady-state operation.
• Integrate with customer identity, data, and engineering systems, as well as infrastructure and model-serving components.
• Partner with customer IT, security, and platform teams during assessments, reviews, and incident response.
• Troubleshoot issues across the deployed environment, including infrastructure and systems outside the platform.
• Write runbooks and post-mortems, improve repeatable deployment guidance, and feed customer learnings back to product teams.
• Operate across managed Kubernetes, on-premises and air-gapped clusters, GPU infrastructure, self-hosted models, and HPC environments.

Requirements

• At least six years of production enterprise software deployment and operations experience, including two years in externally controlled environments.
• Strong Kubernetes configuration and debugging skills, including chart values, rendered manifests, and workload startup issues.
• Understanding of OIDC and SAML, client configuration, credential rotation, redirect URIs, and group-to-role mappings.
• Experience with Linux, networking, TLS, DNS, routing, ingress and egress, certificate chains, and Kubernetes storage.
• A production deployment you personally delivered and supported, plus professional customer-facing English.
• Willingness to travel to US customer locations and work customer schedules; ITAR clearance is required.

Nice to have

• Background in regulated or air-gapped environments, private registries, GPU scheduling, LLM serving, enterprise identity administration, Terraform, GitOps, Prometheus, Grafana, HPC schedulers, ISO 27001 evidence, Python, or PLM/CAD/CAE systems.

Benefits and work setup

The position is based in San Mateo, California, with US customer travel. The source lists a hybrid arrangement (20% remote), paid vacation, medical, vision and dental coverage, and 401(k) matching, alongside a collaborative team and professional development opportunities.