13 days ago
Remote, United StatesSenior
Responsibilities
- Own the Terraform and ArgoCD IaC/GitOps foundation, including ApplicationSets, declarative delivery, self-healing, and recovery.
- Build and operate a multi-tenant, self-service internal developer platform with golden-path onboarding, tenant and environment management, catalogs, and internal tooling.
- Run Kubernetes on AWS GovCloud across environments, including autoscaling, ingress, Gateway API, certificate management, and ALB integration.
- Architect and deploy AIOps/MLOps capabilities for data science and data engineering teams, including GPU scheduling, model training and serving, managed notebooks, GenAI workloads, and ML pipelines.
- Enable a reliable data lakehouse with Trino/Iceberg, Glue, S3, Dagster, dbt, and search capabilities.
- Deliver observability, SLOs, dashboards, alerting, security automation, secrets management, network policy, least-privilege access, vulnerability remediation, and ATO artifacts.
- Partner with government stakeholders and platform tenants, document the platform, maintain runbooks and production-readiness standards, and mentor teammates.
Requirements
- At least 7 years of experience in Platform Engineering, DevSecOps, Site Reliability, or Cloud Engineering, including senior ownership of a production platform.
- Experience building an internal developer platform or PaaS from the ground up for federal clients and taking it through production and ATO.
- Extensive hands-on experience with Kubernetes, Terraform, ArgoCD or Flux, cloud-native and data-platform tooling, and AWS services.
- Deep expertise in Kubernetes/EKS, GitOps, Terraform infrastructure as code, self-service platform design, multi-tenancy, and onboarding automation.
- Strong CI/CD experience with GitLab CI, Jenkins, ArgoCD, and progressive delivery, plus automation and scripting with Python, Bash, and Go.
- Working knowledge of NIST 800-53, FISMA, ATO processes, GovCloud, and regulated environments.
- U.S. citizenship and ability to obtain and maintain a Public Trust are required; active Public Trust is a plus.
- Preferred qualifications include production MLOps/AIOps, SageMaker, Bedrock, Kubeflow, MLflow, Ray, KServe, Triton, Seldon, GPU scheduling, federal health or regulated data programs, lakehouse technologies, FedRAMP, air-gapped environments, policy-as-code, container security, SBOMs, vulnerability scanning, Kubecost, and documentation-practice experience.
Benefits
- Fully remote U.S. position with weekly pay.
- Paid certifications and training for relevant technologies.
- 401(k) with 100% match up to 6%, PTO, medical, dental, vision, life, and disability insurance.
- Gym or fitness membership, home office setup, swag, snacks, and social events.
Tech Stack
Apache AirflowApache SparkAWSBashdbtGitLab CI/CDGoGrafanaJenkinsKubernetesMLflowPrometheusPythonTerraform
Categories
About Rackner
Rackner is a cloud-native software consultancy that delivers DevSecOps, AI/ML, Kubernetes, and edge-computing solutions for startups, enterprises, and U.S. federal agencies across public and private clouds. Founded in 2015 and headquartered in Silver Spring, Maryland, it is privately held and a Kubernetes Certified Service Provider and CNCF member, offering services from cloud and hybrid-cloud development to web/mobile applications supporting mission-critical systems.