Founding Cloud Infrastructure Engineer

About the Role

This is a founding infrastructure engineering role at an early-stage enterprise AI platform startup, where you'll design and build cloud infrastructure entirely from scratch. You'll own architectural decisions end-to-end — from initial design through production — for a semantic platform serving highly regulated industries like insurance, banking, and healthcare. The choices you make here will shape how the company scales for years to come.

What You'll Do

• Design and build cloud infrastructure from the ground up to power an enterprise-grade semantic AI platform.

• Own the full infrastructure lifecycle, from architecture and deployment through scaling and ongoing operations.

• Establish foundational best practices, standards, and tooling in a greenfield environment.

• Build and maintain CI/CD pipelines and deployment automation systems.

• Architect and manage Kubernetes clusters and container orchestration platforms in production.

• Implement infrastructure monitoring, observability, and logging systems.

• Design and manage database infrastructure including relational and NoSQL systems at scale.

• Implement infrastructure security, networking, and access control.

What We're Looking For

• 5+ years of hands-on experience building and operating cloud infrastructure systems in production environments.

• Proven experience designing and deploying infrastructure-as-code using tools such as Terraform, CloudFormation, or Pulumi.

• Strong experience architecting and managing Kubernetes or other container orchestration platforms in production.

• Deep familiarity with at least one major cloud platform (AWS, GCP, or Azure), including networking, storage, compute, and managed services.

• Experience building and maintaining CI/CD pipelines and deployment automation.

• Hands-on experience with observability and monitoring tooling (e.g., Prometheus, ELK, Datadog, or similar).

• Comfort making high-impact architectural decisions independently in an early-stage environment.

• Experience with data infrastructure or data pipeline systems is a plus.

• Background with knowledge graphs, semantic systems, or graph databases is a plus.

• Experience with ML infrastructure or AI/ML platform systems is a plus.

Location

On-site in San Mateo, California, United States. Visa sponsorship is available.