Senior DevOps AI Platform Engineer
GXO Logistics19 days ago
Remote, United StatesSenior
Responsibilities
- Establish the enterprise DevOps operating model, including CI/CD standards, branching strategies, release governance, environment promotion, deployment approvals, and operational handoffs.
- Design, build, and manage secure CI/CD pipelines for AI platform infrastructure, platform services, agents, MCP servers, LiteLLM, Agent Gateway integrations, model-serving components, and supporting services.
- Engineer and operate Kubernetes capabilities on Google Kubernetes Engine, including Helm or Kustomize deployments, autoscaling, networking, workload identity, secrets, ingress/egress, observability, and runbooks.
- Develop reusable Terraform modules, manage infrastructure state, enforce policy guardrails, maintain environment parity, detect configuration drift, and promote infrastructure across environments.
- Implement Google Cloud foundations and lead DevOps enablement, release engineering, Kubernetes operations, pipeline reliability, and developer experience.
- Translate enterprise architecture standards and reference architectures into automated build, test, deployment, and operational processes.
- Enable GKE-based model serving, vLLM or comparable inference runtimes, model tiering infrastructure, and cost-governed platform operations.
- Implement DevSecOps controls including vulnerability and dependency scanning, container hardening, Binary Authorization or equivalent controls, secrets management, audit logging, and secure deployment gates.
- Create standardized developer workflows for provisioning environments, deploying AI agents, publishing MCP services, testing integrations, and promoting code through automation.
- Build platform observability using logs, metrics, traces, dashboards, alerts, SLOs, SLIs, deployment health monitoring, traceability, and cost attribution.
- Automate operational processes and maintain documentation, release checklists, onboarding materials, rollback procedures, break-glass procedures, and escalation processes.
- Support secure integration between the AI platform and Snowflake-governed data access patterns.
Requirements
- Bachelor’s degree in computer science, engineering, information technology, cloud computing, or a related technical field; equivalent hands-on experience may be considered.
- Google Cloud Professional DevOps Engineer certification is required.
- At least 8 years of platform engineering, DevOps, SRE, infrastructure engineering, cloud engineering, or software delivery engineering experience.
- At least 5 years of hands-on Google Cloud Platform experience supporting production environments.
- Deep experience with Google Kubernetes Engine and Kubernetes operations, including workload identity, networking, autoscaling, ingress/egress, Helm or Kustomize, and production troubleshooting.
- Expert experience developing and managing Terraform infrastructure, including reusable modules, state management, CI/CD integration, policy-as-code, infrastructure promotion, and drift management.
- Strong experience with secure CI/CD platforms such as Cloud Build, GitHub Actions, GitLab CI, Azure DevOps, or Jenkins.
- Experience with GitOps and DevSecOps practices, code review automation, dependency scanning, container security, secrets management, signed artifacts, deployment approvals, and security guardrails.
- Experience supporting cloud-native AI, machine learning, analytics, developer platform, or data platform workloads on Kubernetes and Google Cloud.
- Experience with incident response, root cause analysis, observability, production support, SLOs, SLIs, release readiness, and continuous operational improvement.
- Strong technical communication, documentation, collaboration, and cross-functional influence skills.
- Preferred qualifications include HashiCorp Terraform Associate, Certified Kubernetes Administrator, Certified Kubernetes Application Developer, or Google Cloud Professional Cloud Architect, Cloud Security Engineer, or Machine Learning Engineer certifications.
- Preferred experience includes LiteLLM, Agent Gateway, MCP servers, Vertex AI, Gemini, model routing, vLLM, open-source model serving, AI-assisted software development, and large-scale platform standardization.
Benefits
- Full medical, dental, and vision insurance.
- 401(k), life insurance, and disability insurance.
- Opportunity to participate in a company incentive plan.
- Equal Opportunity employer including Disabled/Veterans.
- Conditional offers may require passing a pre-employment drug test.
Tech Stack
Categories
About GXO Logistics
GXO Logistics provides contract logistics services, designing and operating warehouses and fulfillment centers with advanced automation, robotics, and data-driven processes for retailers, e-commerce platforms, consumer goods companies, and manufacturers. Its offerings include e-commerce fulfillment, reverse logistics, and supply chain management. The company was formed in 2021 as a spin-off from XPO Logistics, is headquartered in Greenwich, Connecticut, and is publicly traded on the NYSE.