SecurityScorecardRemote
Senior Site Reliability Engineer
United States of America
Full Time
6 hours ago
$152,000 - $195,000 USD
No H1B
Key skills
Site Reliability EngineeringDevOpsKubernetesAI/LLM toolingMCP serversCI/CD pipelinesGitHub ActionsJenkinsGitLab CIKubernetes internalsEKSGKEAKSInfrastructure as CodeTerraformHelmPulumiGitOpsPythonBashGoObservability toolingPrometheusGrafanaDatadogOpenTelemetryKafkaFlinkClickHouseAILLMMLOpsAnalyticsGitHubGitLabCI/CDCommunicationCollaboration
About this role
SecurityScorecard is the global leader in cybersecurity ratings, and they are seeking a Senior Site Reliability Engineer to drive the design and optimization of their Kubernetes-based infrastructure and CI/CD systems. The role involves building and operating AI tooling infrastructure, optimizing CI/CD pipelines, and leading incident response efforts.
Responsibilities:
- Design, build, and scale Kubernetes infrastructure for secure, multi-tenant, high-availability applications
- Build and operate AI tooling infrastructure — stand up MCP servers and establish secure, governed AI access and guardrails for production systems
- Optimize and maintain CI/CD pipelines, improving reliability, speed, and rollback safety
- Implement progressive delivery strategies such as blue/green and canary deployments
- Advance Infrastructure as Code with Terraform, Helm, and Argo CD, defining reusable patterns for the org
- Operate and optimize streaming and analytics infrastructure: Kafka, Flink, and ClickHouse
- Build automated testing into the CI/CD lifecycle
- Improve system observability — define SLOs, alerts, and dashboards
- Lead incident response and postmortems, focusing on root cause and durable fixes
- Mentor engineers across teams on Kubernetes, CI/CD, and cloud infrastructure
Requirements:
- 6+ years in SRE, DevOps, or Infrastructure roles, with significant production Kubernetes experience
- Hands-on experience integrating AI/LLM tooling into engineering or operational workflows (e.g., MCP servers, AI agents acting on infrastructure), and a clear grasp of the security and governance considerations of giving AI access to production
- Proven success building CI/CD pipelines (GitHub Actions, Jenkins, GitLab CI, or similar)
- Strong with Kubernetes internals and managed services like EKS, GKE, or AKS
- Expertise with Infrastructure as Code (Terraform, Helm, Pulumi) and GitOps
- Proficient in Python, Bash, or Go
- Knowledge of observability tooling (Prometheus, Grafana, Datadog, OpenTelemetry)
- Production experience with Kafka, Flink, and ClickHouse
- Strong communication and cross-team collaboration skills
- Multi-region or multi-cluster Kubernetes experience
- Chaos engineering or resilience testing
- Security scanning, compliance automation, or policy-as-code
- LLM observability/tracing tooling (Langsmith, Langfuse) or MLOps workflows
- Contributions to open-source Kubernetes or CI/CD projects