Principal Cloud Platform Engineer
$210k - $280k • Remote • Austin, Texas, United States; San Jose, California, United States
Posted 17d ago
Job Location
Austin, Texas, United States; San Jose, California, United States
Tech Stack
Remote Work Policy
Fully remote
Categories
AI Infrastructure Engineer
About the job
As a Principal Cloud Platform Engineer, you will specialize in our AI Inferencing Service, acting as the guardian of its reliability, performance, and scalability. You will bridge the gap between software development and operations, applying an engineering mindset to solve operational challenges. Your primary focus will be ensuring our inference endpoints have exceptional uptime, low-latency response times, and efficient resource utilization, directly impacting the experience of our customers and the success of our AI products. This role includes participating in a shared on-call rotation to maintain 24/7 service reliability.
Responsibilities
- Share ownership of the production inferencing service across regions, covering availability, latency, performance, change management, and capacity planning.
- Set up and automate AI infrastructure in new regions.
- Participate in a shared primary/secondary on-call rotation and lead incident response.
- Build monitoring, alerting, and dashboards in Prometheus, Grafana, and Datadog for service health, model latency and throughput, and accelerator utilization.
- Identify and eliminate performance bottlenecks.
- Design auto-scaling policies to handle variable inference loads.
- Manage cloud and on-prem infrastructure as code using Terraform and Ansible.
- Build CI/CD pipelines for safe deployment of new model versions and service updates.
- Forecast infrastructure needs against the product roadmap and usage trends, and collaborate with finance to manage cloud spend.
- Define and report on SLOs and SLIs for the inferencing platform to prioritize reliability work.
Requirements
- B.S. in Computer Science, Computer Engineering, or related field.
- 5+ years of experience in Site Reliability Engineering or DevOps.
- Experience supporting large-scale, customer-facing services in a public cloud environment (AWS, GCP, Azure).
- Strong programming and scripting skills in languages like Python, Go, Rust, or Java.
- Proven experience with containerization and orchestration technologies (Docker and Kubernetes).
- Deep understanding of monitoring and observability principles and tools (e.g., Prometheus, Grafana, ELK Stack, Datadog).
- Experience with Infrastructure as Code (e.g., Terraform, CloudFormation).
- Experience with CI/CD principles and tools (e.g., Jenkins, GitHub Actions, ArgoCD).
- Strong Linux/Unix system administration fundamentals.