10+ years of experience in Infrastructure, DevOps, or Site Reliability Engineering with a proven track record in production systems
Bachelor's or Master's degree in Computer Science, Engineering, or a related field
Deep expertise in Kubernetes, Docker, and container orchestration
Strong proficiency in infrastructure-as-code tools like Terraform, Pulumi, or CloudFormation
Hands-on experience with major cloud providers (AWS, GCP, or Azure)
Solid understanding of observability stacks and incident management
Experience with cloud-native security best practices
Excellent communication skills and ability to work independently or collaboratively
Bonus: Experience with AI/ML or generative AI infrastructure scaling
Responsibilities
Design, deploy, and manage cloud infrastructure on AWS, GCP, or Azure for AI workloads
Build and maintain Kubernetes clusters and container orchestration pipelines
Develop infrastructure-as-code to ensure reproducible environments
Implement observability practices for system health and incident response
Enhance infrastructure security through best practices and compliance controls
Optimize performance and reliability of GPU-intensive workloads
Collaborate with cross-functional teams to define SLOs and improve platform resilience
Automate CI/CD pipelines for efficient deployment
Mentor fellow engineers to foster a strong engineering culture
Benefits
Competitive compensation including salary, equity, and 401(k)
Full medical, dental, and vision insurance for employees and families
HSA and FSA options for financial wellness
Flexible time off including parental leave
Well-being programs for mental and physical health support
Daily lunch and snacks provided
Opportunity to work closely with top AI leaders on impactful products
Full Job Description
What You'll Do
We're looking for a Staff Infrastructure Engineer to help lead core parts of our platform. You'll design, build, and scale the cloud infrastructure that powers our AI and GenAI workloads - ensuring reliability, security, and performance as we grow.
This is your chance to shape the backbone of a platform trusted by Fortune 100 companies - building systems that are resilient, observable, and ready to scale with the next wave of AI.
How You'll Make an Impact:
Design, deploy, and manage production-grade cloud infrastructure on AWS, GCP, or Azure to support AI/GenAI workloads at scale
Build and maintain Kubernetes clusters and container orchestration pipelines for high-availability services
Develop and evolve infrastructure-as-code (Terraform, Pulumi, or similar) to ensure reproducible, auditable environments
Implement comprehensive observability - monitoring, logging, alerting, and tracing - to maintain system health and accelerate incident response
Harden infrastructure security posture through network policies, secrets management, IAM best practices, and compliance controls
Optimize cost, performance, and reliability of GPU and compute-intensive workloads that power generative AI capabilities
Collaborate closely with Product, Engineering, and Security partners to define SLOs and drive continuous improvements in platform resilience
Automate CI/CD pipelines and deployment workflows to enable fast, safe releases across environments
Mentor and support fellow engineers, contributing to a strong infrastructure engineering culture
What You Bring:
10+ years of Infrastructure, DevOps, or Site Reliability Engineering experience, with a strong track record of building and operating production systems at scale
Bachelor's or Master's degree in Computer Science, Engineering, or a related field
Deep expertise with Kubernetes, Docker, and container orchestration in production environments
Strong proficiency with infrastructure-as-code tools such as Terraform, Pulumi, or CloudFormation
Hands-on experience with at least one major cloud provider (AWS, GCP, or Azure), including networking, compute, storage, and identity services
Solid understanding of observability stacks (Prometheus, Grafana, Datadog, or similar) and incident management practices
Experience with security best practices for cloud-native environments - including network segmentation, secrets management, and compliance frameworks
Excellent communication skills and the ability to thrive independently and in collaborative teams
Bonus: Experience scaling infrastructure for AI/ML or generative AI workloads, including GPU orchestration
Location
This is a hybrid role based in Palo Alto, CA. We collaborate in-office 3 days a week.
Base Salary
The range for this role is $210,000-$240,000 plus equity. Actual compensation may vary based on level, experience, and skillset as assessed in the interview process.
Benefits
Competitive compensation - including salary, equity, and 401(k)
Full medical, dental, and vision insurance for you and your family
HSA and FSA options to support your financial wellness
Flexible time off - including parental leave
Well-being programs - resources to support your mental and physical health
Daily lunch & snacks
Mentorship & impact - work closely with top AI leaders on products that ship
