Senior DevOps Engineer - AI Platform, Multi-Cloud & Edge

webAI; États-Unis; À distance; USD 150 000 - 210 000; Plein temps

Avantages offerts par ce poste

Equity options

Parental leave

401(k) plan

Health coverage

Learning stipend

Remote-first with flexible time off

Résumé du poste

webAI seeks a Senior DevOps Engineer to design, build, and scale secure infrastructure supporting AI workloads across cloud, hybrid, and edge environments. You will drive architecture, platform reliability, and security across the org.

You will work closely with engineering teams to implement scalable, automated infrastructure solutions enabling the AI platform to operate efficiently—from public cloud to edge deployments.

Qualifications

• 5–8+ years of DevOps, SRE, or infrastructure engineering experience.
• Hands-on with multi-cloud (AWS/Azure/GCP) and edge deployments.
• Proficient in IaC (Terraform, Pulumi, Ansible) and GitOps.
• Experience building CI/CD pipelines (GitHub Actions, GitLab CI, Jenkins, ArgoCD).
• Strong automation, security, and cost-optimization practices.

Responsabilités

• Design, build, and scale secure infra for AI workloads.
• Implement scalable, automated infrastructure across cloud, hybrid, and edge.
• Deploy and operate Kubernetes clusters for AI/ML workloads.
• Develop secure CI/CD pipelines with integrated security controls.
• Support MLOps infrastructure initiatives including model deployment automation.
• Implement observability and monitoring.
• Enforce IAM, encryption, network segmentation, and compliance automation.
• Mentor junior engineers on DevOps practices.

Connaissances

DevOps

SRE

Kubernetes

Docker

CI/CD

Python

Cloud platforms

Security practices

Outils

Terraform

Pulumi

Ansible

GitHub Actions

GitLab CI

Jenkins

ArgoCD

Istio

Linkerd

Description du poste

webAI seeks a Senior DevOps Engineer to design, build, and scale secure infrastructure supporting AI workloads across cloud, hybrid, and edge environments. You will drive architecture, platform reliability, and security across the org.

You will work closely with engineering teams to implement scalable, automated infrastructure solutions enabling the AI platform to operate efficiently—from public cloud to edge deployments.