Platform Engineer — Enterprise AI Deployment & Infra

Remanence

Paris

Hybride

EUR 110 000 - 150 000

Plein temps

Il y a 10 jours
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Avantages offerts par ce poste

Competitive compensation and equity
Fast-paced, impactful environment
Visa sponsorship and relocation for巴黎/
Hybrid work setup

Résumé du poste

Remanence is building a platform engineering team to deploy its AI platform across customer infrastructures, including on-premise and cloud environments. You will design CI/CD, deployment tooling, and observability to enable reliable operations in varied networks.

The role requires hands-on experience with Kubernetes and Terraform in production systems. We welcome engineers who can translate complex deployment constraints into robust, repeatable processes, and who enjoy collaborating with

Qualifications

  • Shipped software that runs reliably outside infra you control.
  • Experience deploying in enterprise or security-sensitive environments.

Responsabilités

  • Package the Remanence stack for deployment on-premise and in customer-owned clouds.
  • Design and maintain IaC and deployment layer with Terraform, Helm, Kubernetes operators.
  • Own CI/CD, release engineering, and upgrade paths; automate installations and migrations.
  • Build observability and diagnostics tooling for operable deployments without direct customer access.
  • Collaborate with Infrastructure and Research on sandboxed execution, GPU scheduling, and resource isolation.

Connaissances

Systems fundamentals
Observability
Debugging
Upgrade paths

Outils

Kubernetes
Terraform
Helm
Argo CD
Flux
OpenShift

Description du poste

Remanence is building a platform engineering team to deploy its AI platform across customer infrastructures, including on-premise and cloud environments. You will design CI/CD, deployment tooling, and observability to enable reliable operations in varied networks.

The role requires hands-on experience with Kubernetes and Terraform in production systems. We welcome engineers who can translate complex deployment constraints into robust, repeatable processes, and who enjoy collaborating with

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