3 days ago
Responsibilities
- Design and build cloud infrastructure from the ground up for an enterprise semantic AI platform.
- Own infrastructure architecture, deployment, scaling, and ongoing production operations.
- Establish foundational infrastructure best practices, standards, and tooling.
- Build and maintain CI/CD pipelines and deployment automation systems.
- Architect and manage production Kubernetes clusters and container orchestration platforms.
- Implement monitoring, observability, and logging systems.
- Design and manage relational and NoSQL database infrastructure at scale.
- Implement infrastructure security, networking, and access control.
Requirements
- 5+ years of hands-on experience building and operating production cloud infrastructure systems.
- Experience designing and deploying infrastructure-as-code with Terraform, CloudFormation, Pulumi, or similar tools.
- Strong production experience architecting and managing Kubernetes or other container orchestration platforms.
- Deep familiarity with 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 tools such as Prometheus, ELK, or Datadog.
- Ability to make 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.
Benefits
- On-site role in San Mateo, California, United States.
- Visa sponsorship is available.