Platform Deployment Engineer - West Coast

Neural Concept

1d • $200,000 - $250,000 • Hybrid

About The Position

The Platform Deployment Engineer owns end-to-end deployment and operation of Neural Concept’s platform for named enterprise customer accounts, serving as each customer’s primary technical counterpart. The role spans initial architecture discussions, deployment, integrations, security clearance, go-live, and steady-state operations.

The engineer works with customer identity, data, and engineering systems, as well as the infrastructure and model-serving layers beneath the platform. They partner with customer IT, security, and platform teams on assessments and architecture reviews, and diagnose incidents even when the cause is outside Neural Concept’s software. They also create runbooks, post-mortems, and playbooks to improve future deployments and provide feedback to Product.

Deployments may involve managed Kubernetes on major cloud providers, on-premises or fully air-gapped clusters, GPU infrastructure, self-hosted model serving, and customer HPC environments, schedulers, and shared storage. The role is based in San Mateo, California, requires travel to customer locations in the US, and requires ITAR clearance. The stated start date is ASAP.

Requirements

• At least 6 years of experience deploying and operating enterprise software in production, including at least 2 years in environments the candidate did not control.
• Kubernetes knowledge at configuration depth, including understanding how chart values become rendered manifests and diagnosing why workloads do not start.
• Knowledge of identity and SSO fundamentals, including OIDC, SAML, clients, credential rotation, redirect URIs, and group-to-role mapping.
• Knowledge of Linux, networking, and TLS, including DNS, routing, ingress and egress, certificate chains, and interception proxies.
• Knowledge of Kubernetes storage, including persistent volumes, CSI, access modes, and diagnosing shared storage degradation under load.
• A production deployment personally carried through and subsequently supported; candidates should be prepared to name and date it and explain what went wrong.
• Professional customer-facing English.
• Willingness to travel and work customers’ hours.
• ITAR clearance required.

Nice To Haves

• Experience with regulated or air-gapped deployments.
• Experience with private registries and image mirroring.
• Experience with GPU scheduling and LLM serving.
• Enterprise identity provider administration experience.
• Terraform and GitOps experience.
• Prometheus and Grafana experience.
• Experience with HPC schedulers.
• Experience with ISO 27001 evidence.
• Python experience.
• PLM, CAD, or CAE exposure.

Responsibilities

• Own customer deployments from initial architecture discussions through go-live and steady-state operation.
• Integrate the platform with customer identity, data, and engineering systems, and with the underlying infrastructure and model-serving layer.
• Serve as the primary technical counterpart for named customer accounts and work with customer IT, security, and platform teams.
• Participate in customer assessments and architecture reviews.
• Diagnose and resolve deployment and operational issues, including issues caused by systems outside Neural Concept’s software.
• Create runbooks, post-mortems, and playbooks to improve subsequent deployments.
• Provide customer deployment feedback to the Product team.

Benefits

• Competitive salary and rewarding opportunities as the company scales.
• Collaborative, multicultural environment where work is visible and recognized.
• Professional development alongside colleagues who share knowledge and support one another.
• Remote work or a hybrid model (20% remote), with emphasis on results rather than rigid schedules.
• Paid vacations.
• Healthcare, including medical, vision, and dental.
• 401K matching.

What This Job Offers

• Job Type: Full-time
• Education Level: No Education Listed