Enterprise Platform Deployment Engineer - Kubernetes

Neural Concept; Jersey City (NJ); On-site; USD 150,000 - 190,000; Full time

Benefits offered by this job

Healthcare (medical)

Paid vacations

401K matching

Remote/hybrid options (20% remote)

Job summary

Neural Concept seeks an experienced engineer to take an enterprise customer and make the platform real in their environment, under their rules. You will own deployment end-to-end, from architecture discussions to go-live and steady-state operation, including integration with identity, data, and model serving layers.

You will work with customer IT, security, and platform teams, perform architecture reviews, and drive incident diagnosis and resolution.

Qualifications

• Must have 6+ years deploying and operating enterprise software in production, with at least two years in environments you did not control.
• Deep Kubernetes configuration and troubleshooting skills (rendered manifests from chart values, failed workloads).
• Solid Identity and SSO fundamentals: OIDC, SAML, rotation, redirect URIs, group-to-role mapping.
• Strong Linux, networking and TLS knowledge including DNS, routing, ingress/egress, TLS chains.
• Kubernetes storage experience with persistent volumes and CSI, shared storage under load.
• Proven production deployment experience and ability to own incidents end-to-end.

Responsibilities

• Lead deployment from architecture conversations through go-live and steady state.
• Integrate with customer identity, data, engineering systems, and model serving layers.
• Coordinate with customer IT, security, and platform teams; conduct architecture reviews and incident response.
• Diagnose outages, including root cause analysis beyond our own software.
• Create runbooks, post-mortems, and feedback loops to Product for future deployments.

Job description

Neural Concept seeks an experienced engineer to take an enterprise customer and make the platform real in their environment, under their rules. You will own deployment end-to-end, from architecture discussions to go-live and steady-state operation, including integration with identity, data, and model serving layers.

You will work with customer IT, security, and platform teams, perform architecture reviews, and drive incident diagnosis and resolution.