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Rackner

DevSecOps and AI for cloud-native edge

Platform Engineer

Platform EngineeringConfirmed live in the last 24 hours
Full-timeRemote in USANo salary listed

About the Job

Requirements

  • At least 7 years of experience in Platform Engineering, DevSecOps, Site Reliability, or Cloud Engineering, including senior-level 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 in a federal program.
  • Hands-on experience with cloud-native and data ecosystem technologies, including Kubernetes, Terraform, ArgoCD, Karpenter or KEDA, Prometheus, Grafana, Loki, Trino, Dagster, and dbt, as well as AWS services including EKS, S3, Glue, IAM/IRSA, ECR, SageMaker, Bedrock, and Athena.
  • Deep expertise with Kubernetes (EKS), GitOps (ArgoCD or Flux), and Terraform infrastructure-as-code.
  • Experience designing self-service golden paths, multi-tenancy, and onboarding that enables teams to ship safely without a platform engineer in the loop.
  • Strong CI/CD background with GitLab CI, Jenkins, ArgoCD, and progressive delivery.
  • Fluency in automation and scripting with Python, Bash, and Go.
  • Working knowledge of federal compliance, including NIST 800-53, FISMA, and ATO processes, and comfort working in GovCloud or regulated environments.
  • Ability to produce clear documentation and runbooks and treat knowledge transfer as part of completing work.
  • U.S. citizenship is required, and the candidate must be able to obtain and maintain a Public Trust.
  • Ability to work client-facing, wear many hats, and mentor teammates.

Responsibilities

  • Own and evolve the infrastructure-as-code and GitOps foundation using Terraform and ArgoCD ApplicationSets so the platform is declarative, self-healing, and recoverable from scratch.
  • Build and operate a multi-tenant, self-service platform, including golden-path application onboarding, tenant and environment management, an application and tooling catalog, and internal developer tooling or a CLI.
  • Run Kubernetes on AWS GovCloud, including Karpenter and KEDA autoscaling, ingress and Gateway API, cert-manager, and ALB integration across development, pre-production, and production.
  • Architect and deploy AIOps/MLOps for data science and data engineering teams, including GPU compute and scheduling, model training and serving, managed notebooks such as SageMaker, GenAI/Bedrock workloads, and production-grade machine-learning pipelines.
  • Enable the data lakehouse using Trino/Iceberg on Glue and S3, Dagster orchestration, dbt, and search to provide reliable, performant data access.
  • Deliver observability and SLOs using Prometheus and Grafana, including custom-built dashboards and actionable alerting.
  • Automate security and compliance through secrets management, network policy, least-privilege IRSA, policy-as-code, vulnerability remediation, and ATO artifact generation.
  • Author and maintain platform documentation, production-readiness standards, and runbooks, and drive knowledge transfer.
  • Partner directly with government stakeholders and platform tenants to translate mission needs into platform capabilities.

Desired Qualifications

  • Hands-on production MLOps/AIOps experience for data science or data engineering teams using SageMaker, Bedrock, Kubeflow, MLflow, Ray, KServe, Triton, Seldon, or GPU workload scheduling.
  • Experience with federal health or other regulated federal data programs.
  • Data platform or lakehouse experience with Trino/Presto, Iceberg, Spark, Dagster/Airflow, or dbt.
  • Experience with AWS GovCloud, IL4/IL5, FedRAMP, or air-gapped environments.
  • Experience with policy-as-code tools such as OPA/Gatekeeper or Kyverno, container security, SBOMs, and vulnerability scanning.
  • Experience with Kubecost or cloud cost management.
  • Experience establishing a documentation practice and production-readiness standards.

About the Company

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Rackner

DevSecOps and AI for cloud-native edge

Rackner provides services that blend DevSecOps with artificial intelligence to help organizations run workloads in the datacenter, public and private clouds, and at the edge. Its offerings center on automating secure software delivery (devsecops), building cloud-native and hybrid-cloud applications, and extending compute to edge environments using technologies like Kubernetes and WebAssembly. The company supports both fast-growing startups and federal agencies, including Civilian and Defense sectors, and differentiates itself through its deep focus on security, cloud-native architecture, edge computing, and AI/ML capabilities, along with its status as a Cloud Native Computing Foundation member, Kubernetes Certified Service Provider, and partner to major cloud providers. Rackner’s goal is to help customers deliver scalable, secure, and efficient software and AI-powered applications across on-premises, cloud, and edge environments.

Company size
11-50
Company stage
Not listed
Total funding
Not listed
Headquarters
Washington DC, District of Columbia
Founded
2015

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