SlipstreamJobs tracks this role from the company's public career site. Apply directly on the employer's site.
Salary: USD 210,000 - 240,000 / annual
Typeface is an AI-powered marketing orchestration platform trusted by Fortune 100 companies, backed by Microsoft, GV, Salesforce, Lightspeed, Madrona, and Menlo. The company helps enterprises move from brief to fully personalized campaigns in days rather than months.
You will design, build, and scale the cloud infrastructure powering Typeface's AI and GenAI workloads. This is a Staff-level individual contributor role where you'll lead core infrastructure initiatives, ensuring reliability, security, and performance as the platform scales.
Key responsibilities:
- Design, deploy, and manage production-grade cloud infrastructure on AWS, GCP, or Azure for 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 powering generative AI
- Collaborate with Product, Engineering, and Security teams to define SLOs and drive continuous improvements in platform resilience
- Automate CI/CD pipelines and deployment workflows to enable fast, safe releases
- Mentor and support fellow engineers, contributing to a strong infrastructure engineering culture
The role is hybrid, based in Palo Alto with 3 days per week in-office collaboration.
REQUIREMENTS:
- 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 related field
- Deep expertise with Kubernetes, Docker, and container orchestration in production environments
- Strong proficiency with infrastructure-as-code tools (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—network segmentation, secrets management, and compliance frameworks
- Excellent communication skills and ability to thrive independently and in collaborative teams
- Bonus: Experience scaling infrastructure for AI/ML or generative AI workloads, including GPU orchestration
