Platform Deployment Engineer - West Coast

Neural Concept; United States; Híbrido; USD 200 000 - 250 000; Tempo integral

Vantagens oferecidas por esta oferta de emprego

Competitive salary

Remote or hybrid model (20% remote)

Healthcare (medical/vision/dental)

401K matching

Resumo da oferta

Neural Concept is seeking an experienced engineer to deploy and operate enterprise AI platforms for named customers. You will own deployments from architecture conversations to live, secure, and scalable operations inside customer environments.

You will coordinate identity integration, data flows, and model serving, aligning with IT, security, and platform teams to ensure reliability and performance across cloud and on-premises clusters.

Qualificações

• 5+ years deploying and operating enterprise software in production.
• Experience with Kubernetes at depth (chart values to manifests).
• Knowledge of OIDC and SAML identity protocols and credential rotation.
• Strong Linux networking and TLS fundamentals.
• Hands-on Kubernetes storage (CSI, PVs, access modes) and load considerations.
• Proven track record deploying and supporting a production system end-to-end.
• Excellent professional English communication and willingness to travel.

Responsabilidades

• Lead deployment from architecture through go-live and steady-state operation.
• Integrate with customer IT, security, data, and model-serving infrastructure.
• Collaborate with customer IT/security/platform teams and perform architecture reviews.
• Diagnose issues beyond our software boundaries and drive resolution.
• Create runbooks, post-mortems, and playbooks to improve future deployments.

Conhecimentos

Enterprise deployment

Kubernetes expertise

Identity/SSO (OIDC/SAML)

Linux networking TLS

Kubernetes storage CSI

Customer-facing communication

Willingness to travel

Ferramentas

Terraform

GitOps

Prometheus/Grafana

HPC schedulers

Descrição da oferta de emprego

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

• 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

• San Mateo, California;
• 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.

Compensation Range: $200K - $250K