Rackner

Platform Engineer

• Build and operate a secure, cloud-native platform powering data, analytics, and AI/ML for a federal health mission
• Own and evolve the Terraform and ArgoCD IaC/GitOps foundation
• Build and operate a multi-tenant, self-service platform with golden-path onboarding, tenant/environment management, application and tooling catalog, and internal developer tooling/CLI
• Run Kubernetes on AWS GovCloud across development, pre-production, and production
• Implement Karpenter and KEDA autoscaling, ingress, Gateway API, cert-manager, and ALB integration
• Architect and deploy AIOps/MLOps capabilities for data science and data engineering teams
• Enable GPU compute and scheduling, model training and serving, managed notebooks, GenAI/Bedrock workloads, and production ML pipelines
• Build the data lakehouse using Trino/Iceberg on Glue and S3, Dagster, dbt, and search
• Deliver observability and SLOs using Prometheus and Grafana, including custom dashboards and actionable alerting
• Automate security and compliance through secrets management, network policy, IRSA least privilege, policy-as-code, vulnerability remediation, and ATO artifact generation
• Author and maintain platform documentation, production-readiness standards, and runbooks
• Partner directly with government stakeholders and platform tenants to translate mission needs into platform capabilities
• Mentor teammates and grow into a technical leadership role