Listed on Levi Strauss & Co.’s own careers site. You apply with them directly — we never stand between you and the employer.
What this role is
A Site Reliability Engineer will ensure data and AI platforms serving Levi Strauss's global retail operations remain available, performant, and secure on Google Cloud Platform and supporting infrastructure. This role suits engineers with production SRE experience who want to grow their reliability craft while collaborating with data and AI teams in a multi-cloud environment.
Our summary, not Levi Strauss & Co.’s wording. The full posting is on their site.
Skills this role names
- ArgoCD
- Bash (Scripting)
- Datadog
- GitHub Actions
- Go
- Google BigQuery
- Google Cloud Platform
- Google Cloud Storage
- Grafana
- Helm
- Kubernetes
- Prometheus
- Python
- Terraform
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What they ask for
Required
- Bachelor's degree in Computer Science, Engineering, or related field or equivalent practical experience
- 6+ years of Site Reliability Engineering, DevOps, or Platform/Infrastructure Engineering in production environments
- Hands-on experience with GCP services including GKE, Cloud Run, BigQuery, Pub/Sub, and GCS
- Working proficiency with Infrastructure-as-Code tools such as Terraform or Helm
- Familiarity with observability tooling for metrics, logging, tracing, and alerting
- Understanding of SLO/SLI concepts and their relation to production reliability
- Exposure to data security fundamentals including IAM, encryption, secrets management, and network policies
- Proficiency in at least one scripting or systems language for automation
- Strong communication skills for documenting incidents, runbooks, and technical processes
- Experience with container orchestration and Kubernetes operational patterns
Nice to have
- Experience working in retail, e-commerce, or consumer goods environments
- Familiarity with Google's SRE principles including error budgets and production readiness reviews
- Exposure to AI or ML platform operations and model serving infrastructure monitoring
- Experience with FinOps or cloud cost visibility tooling
- Basic understanding of CI/CD pipelines and GitOps workflows
- Comfort working with data platforms and familiarity with batch or streaming data pipelines
- Awareness of multi-cloud concepts across GCP and Azure