This role pays more than
57%
of similar roles. Most pay
$160,300–$246,150
— the shaded band above.
At the midpoint, this role pays about
$218k
versus about
$203k
for comparable roles.
Based on 240 similar postings.
Employer
About SentinelOne
SentinelOne is a cybersecurity company that provides an AI-powered extended detection and response (XDR) platform. Its Singularity platform delivers autonomous endpoint, cloud, and identity protection for enterprises.
SentinelOne currently has
11 open roles
on FindRole.
Listed pay typically runs
$132,000–$160,000
across 7 roles with salary data.
As a Senior Staff AI Platform Engineer, you will join the platform team to serve as a hands-on builder of the enterprise AI platform, including the Gateway, Harness, and Semantic Layers. You will write production code to govern, observe, secure, and scale AI activity across the company by designing and operating scalable cloud infrastructure on GCP and AWS. Your daily work involves managing Kubernetes-based runtime environments, developing Infrastructure as Code using Terraform, and maintaining CI/CD and GitOps workflows via tools like GitHub Actions or Argo CD. You will specifically own Kong Gateway capabilities, including routing, authentication, and rate limiting. To succeed, you must possess expertise in Python, Go, or Bash, along with deep knowledge of cloud networking, observability practices, and secure infrastructure components like IAM and secrets management to support AI gateway and model-serving capabilities.
Design and operate secure, scalable cloud infrastructure on GCP and AWS to support Enterprise AI Platform services.
Build and manage Kubernetes-based runtime environments for platform services, APIs, gateways, and agents.
Develop reusable Infrastructure as Code using Terraform to manage cloud resources, networking, and IAM.
Create and maintain CI/CD and GitOps workflows to ensure consistent deployment and rollback across environments.
Own the Kong Gateway infrastructure, including scaling, routing, authentication, and lifecycle management.
Establish automated standards for onboarding and managing APIs through the Kong Gateway.
Implement security measures such as least-privilege access, secrets management, and secure software supply-chain practices.
Build platform observability systems including metrics, logging, distributed tracing, and alerting dashboards.
What we're looking for
8 or more years of professional engineering experience in platform engineering, cloud infrastructure, DevOps, SRE, or production infrastructure.
Strong hands-on experience with Google Cloud Platform (GCP) including networking, IAM, compute, and storage; AWS experience is also valuable (preferred).
Deep practical experience with Kubernetes in production for deployments, services, ingress, autoscaling, and troubleshooting.
Strong Infrastructure as Code experience, preferably using Terraform to manage reusable modules and multi-environment infrastructure.
Hands-on experience with modern CI/CD and GitOps tooling such as GitHub Actions, Argo CD, GitLab CI, or Jenkins.
Strong hands-on experience operating Kong Gateway or comparable API gateway technologies in production.
Working proficiency in Python, Go, Bash, or other scripting languages for automation.
Experience supporting AI/ML platforms, AI gateways, model-serving infrastructure, or vector databases (preferred).
AWS
Kubernetes
Docker
Terraform
CloudFormation
Python
CI/CD
Infrastructure as Code
MLOps
Amazon Bedrock
SageMaker
DevSecOps
RMF
Platform One
Iron Bank
Big Bang
FedRAMP
IL5
Python
Terraform
AWS
Azure
Google Vertex AI
OpenAI
AWS Bedrock
GenAI
LLM
Infrastructure as Code
Prompt Engineering
Agentic AI
Tofu
Env0
Test-Driven Development