AI-Native DevOps Lead for AI SaaS Platform

ServiceNow; California; Remote; USD 201,000 - 352,000; Full time

Benefits offered by this job

Health plans

401(k) Plan with company match

ESP P / equity eligibility

Job summary

ServiceNow is seeking a Staff AI-Native DevOps Engineer to lead a new DevOps practice for the Conversational AI team. You will own build, deployment, and reliability across SaaS environments, spanning CI/CD, release automation, and Kubernetes-based infrastructure.

You will collaborate with scientists and engineers to make AI-native delivery repeatable, measurable, and secure, applying cloud, containerization, and IaC principles to production ML and LLM-based services.

Qualifications

• Deep experience designing and operating scalable cloud-native apps and infra.
• Strong software engineering skills with infra tooling and automation.
• Experience leading complex infrastructure initiatives across teams.
• Understanding of modern AI technologies and production integration.
• AI-native engineering mindset to improve delivery and reliability.

Responsibilities

• Deploy, scale, and operate distributed microservices in production Kubernetes environments.
• Design and implement IaC and Kubernetes-native tooling (Terraform, Ansible, Helm).
• Build and maintain CI/CD pipelines and GitOps workflows (Jenkins, GitHub Actions, Tekton, ArgoCD).
• Implement observability and incident response to improve availability and resilience.
• Architect and optimize cloud infra with emphasis on security and cost efficiency.

Skills

Cloud-native design

Go/Python

Kubernetes

DevOps leadership

AI/ML understanding

Problem-solving

Tools

Terraform

Ansible

Helm

Kubernetes Operators

GitHub Actions

Job description

ServiceNow is seeking a Staff AI-Native DevOps Engineer to lead a new DevOps practice for the Conversational AI team. You will own build, deployment, and reliability across SaaS environments, spanning CI/CD, release automation, and Kubernetes-based infrastructure.

You will collaborate with scientists and engineers to make AI-native delivery repeatable, measurable, and secure, applying cloud, containerization, and IaC principles to production ML and LLM-based services.