General DynamicsRemote
Site Reliability Engineer
United States of America
Full Time
6 hours ago
$143,000 - $158,000 USD
No H1B
Key skills
Site Reliability EngineeringDevOpsMonitoring and ObservabilityPrometheusGrafanaDatadogELKCloudWatchPythonBashInfrastructure as CodeTerraformCloudFormationDockerKubernetesService Level Objectives (SLOs)Error BudgetsIncident ResponseAI/ML Production SystemsAWSAzureGCPOperational Readiness ReviewsIncident ManagementPost-Incident ReviewAIMLCI/CD
About this role
General Dynamics Mission Systems is a leader in high technology solutions for defense and scientific arenas. They are seeking a Site Reliability Engineer to define service level objectives, build monitoring infrastructure, and manage incident response for AI services.
Responsibilities:
- Define service level objectives for every AI service that goes to production
- Establish error budgets and use them to drive engineering decisions — not just measure uptime
- Build and maintain monitoring, logging, and alerting infrastructure for AI services
- Establish incident management procedures, lead post-incident reviews, and drive corrective actions
- Validate that it meets reliability, security, and operational standards
- Track resource consumption, forecast capacity needs, and monitor costs
- Identify and automate repetitive operational tasks
Requirements:
- Bachelor's degree in Computer Science, Software Engineering, or a related field, plus 8 years of experience; or Master's degree plus 6 years of experience
- Production SRE or DevOps experience — you have owned the reliability of systems that real users depended on, not just built CI/CD pipelines
- Hands-on experience with monitoring and observability tools — Prometheus, Grafana, Datadog, ELK, CloudWatch, or similar. You have built dashboards and alerts that caught real problems
- Strong scripting and automation skills — Python, Bash, infrastructure-as-code (Terraform, CloudFormation, or similar)
- Experience with containerized environments — Docker, Kubernetes, container orchestration at scale
- Experience defining and managing SLOs, error budgets, and incident response procedures in production
- U.S. citizenship required. Department of Defense Secret security clearance is required at time of hire
- Experience with AI/ML production systems — model serving, inference monitoring, token cost tracking, or similar
- Multi-cloud experience (AWS, Azure, GCP) including cloud-native monitoring and logging services
- Experience building operational readiness review processes or production launch checklists
- Familiarity with Google SRE principles — you have read the book and applied the concepts, not just referenced them in interviews
- Experience in environments where reliability has compliance or safety implications — defense, healthcare, finance, or critical infrastructure