Senior DevOps AI Platform Engineer
New
G
GXOSupply Chain Technology
Remote, NC, USFull-TimeSenior
SalaryCompetitive compensation and a generous benefits package, including full health insurance (medical, dental and vision), 401(k), life insurance, disability and the opportunity to participate in a company incentive plan.
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Job Details
- Experience
- Minimum of 8 years of platform engineering, DevOps, Site Reliability Engineering (SRE), infrastructure engineering, cloud engineering, or software delivery engineering experience; Minimum of 5 years of hands-on Google Cloud Platform experience.
- Required Skills
- GCPKubernetesCI/CDTerraform
Requirements
- Bachelor’s degree in Computer Science, Engineering, IT, Cloud Computing, or related field.
- Google Cloud Professional DevOps Engineer certification.
- Minimum of 8 years of experience in platform engineering, DevOps, SRE, or cloud/software delivery engineering.
- Minimum of 5 years of hands-on Google Cloud Platform experience in production environments.
- Deep expertise in GKE (Google Kubernetes Engine), including workload identity, networking, and autoscaling.
- Expertise in Terraform (reusable modules, state management, CI/CD integration).
- Proficiency in CI/CD platforms such as Cloud Build, GitHub Actions, or GitLab CI.
- Experience implementing GitOps and DevSecOps, including container security and signed artifacts.
- Experience supporting cloud-native AI, machine learning, or data platform workloads.
- Strong operational mindset (incident response, root cause analysis, SLOs/SLIs).
- Excellent technical communication skills for engineering documentation and standards.
Responsibilities
- Establish the enterprise DevOps operating model for GXO's Agentic AI Platform.
- Design and manage secure CI/CD pipelines supporting AI platform infrastructure and model-serving components.
- Operate Kubernetes-based capabilities on Google Kubernetes Engine (GKE).
- Own Terraform infrastructure delivery, including module development and state management.
- Implement enterprise DevSecOps controls like vulnerability scanning and secrets management.
- Create 'paved road' developer workflows for environment provisioning and deployment.
- Build comprehensive observability using logs, metrics, traces, and SLOs/SLIs.
- Automate operational processes to improve incident response and system reliability.
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