DevOps Engineer - Cloud, Kubernetes & CI/CD for AI Safety

Whitecircle; Paris; Hybride; EUR 70 000 - 110 000; Plein temps

Avantages offerts par ce poste

Equity package

Relocation package

Paid time off

Medical insurance (France)

Equipment provided

Résumé du poste

White Circle is an AI Safety company building the safety, reliability, and optimization layer for AI systems. We design, build, and maintain production infrastructure across AWS and on‑prem environments, focusing on reliability, security, and scalability.

This role involves managing Kubernetes clusters, CI/CD pipelines, and tooling to accelerate safe model deployment. You will work closely with engineering and ML teams to support product infrastructure, monitor performance, and implement

Qualifications

• Hands-on experience with AWS services (IAM, S3, EKS, ECR).
• Strong Unix/Linux fundamentals and production troubleshooting.
• Experience building secure, scalable CI/CD pipelines.
• Proficient in Python for automation and tooling.
• Familiar with Terraform and Infrastructure-as-Code (IaC).

Responsabilités

• Design, build, and maintain production infrastructure across AWS and on‑prem environments.
• Manage and improve Kubernetes clusters for deployments, scaling, reliability, and day-to-day operations.
• Build and maintain CI/CD pipelines to ship safer, faster, and more predictable releases.
• Develop and maintain tooling for automation and observability.
• Collaborate with engineering/ML teams to support compute-heavy workloads.

Connaissances

AWS

Kubernetes

Python

Unix/Linux

Networking

CI/CD

Observability

Terraform

Security

Outils

Terraform

Docker

Kubernetes

Datadog

CI/CD tooling

Description du poste

White Circle is an AI Safety company building the safety, reliability, and optimization layer for AI systems. We design, build, and maintain production infrastructure across AWS and on‑prem environments, focusing on reliability, security, and scalability.

This role involves managing Kubernetes clusters, CI/CD pipelines, and tooling to accelerate safe model deployment. You will work closely with engineering and ML teams to support product infrastructure, monitor performance, and implement