You will own and evolve the internal developer platform, focusing on secure, cloud-native infrastructure and MLOps pipelines. You will also partner with government stakeholders to translate mission needs into scalable, self-service platform capabilities.
Senior Platform Engineer Location: Remote (U.S.) Clearance: U.S. Citizenship required; must be able to obtain and maintain a Public Trust (active Public Trust a plus) Employment Type: Full-time
Make an Impact on Federal Health:
Join Rackner to build and operate the secure, cloud-native platform that powers data, analytics, and AI/ML for a federal health mission.
You won't just run infrastructure — you'll own the internal developer platform that data scientists, data engineers, and application teams build on every day.
Shape where it goes next: production-grade MLOps, self-service onboarding, and a paved road from commit to GovCloud.
Who You Are:
7+ years in Platform Engineering, DevSecOps, Site Reliability, or Cloud Engineering, with senior-level ownership of a production platform
Built an internal developer platform / PaaS from the ground up for federal clients — and taken it to production (through ATO) in a federal program, not just contributed to one
Extensive hands-on experience across both the open-source cloud-native/data ecosystem (Kubernetes, Terraform, ArgoCD, Karpenter/KEDA, Prometheus/Grafana/Loki, Trino, Dagster, dbt) and the AWS services that back them (EKS, S3, Glue, IAM/IRSA, ECR, SageMaker, Bedrock, Athena)
Deep expertise with Kubernetes (EKS), GitOps (ArgoCD or Flux), and Terraform infrastructure-as-code
Designs for self-service: golden paths, multi-tenancy, and onboarding that lets teams ship safely without a platform engineer in the loop
Strong CI/CD background (GitLab CI, Jenkins, ArgoCD, and progressive delivery)
Fluent automation and scripting (Python, Bash, Go)
Working knowledge of federal compliance (NIST 800-53, FISMA, ATO processes); comfortable in GovCloud/regulated environments
Treats documentation and knowledge transfer as part of "done" — clear docs and runbooks come naturally
A people person and problem-solver who's comfortable being client-facing, wearing many hats, mentoring teammates, and growing into technical leadership
What You'll Do:
Own the IaC + GitOps foundation — evolve Terraform and ArgoCD (ApplicationSets) so the platform is declarative, self-healing, and recoverable from scratch
Build and operate a multi-tenant, self-service platform — golden-path app onboarding, tenant/environment management, an app & tooling catalog, and internal developer tooling/CLI
Run Kubernetes on AWS GovCloud — Karpenter and KEDA autoscaling, ingress and Gateway API, cert-manager, and ALB integration across dev/pre-prod/production
Architect and deploy AIOps/MLOps for data science and data engineering teams — GPU compute and scheduling, model training and serving, managed notebooks (e.g., SageMaker), GenAI/Bedrock workloads, and production-grade ML pipelines
Enable the data lakehouse — Trino/Iceberg on Glue + S3, Dagster orchestration, dbt, and search — so teams have reliable, performant data access
Deliver observability and SLOs — Prometheus, Grafana (including custom-built dashboards), and actionable alerting
Automate security and compliance — secrets management, network policy, IRSA least-privilege, policy-as-code, vulnerability remediation, and ATO artifact generation
Drive documentation and knowledge transfer — author and maintain platform docs, production-readiness standards, and runbooks
Partner directly with government stakeholders and platform tenants — translate mission needs into platform capabilities, with room to grow into a technical leadership role
Preferred / Bonus:
Hands-on MLOps/AIOps production experience for DS/DE teams — SageMaker, Bedrock, Kubeflow, MLflow, Ray, KServe/Triton/Seldon, or GPU workload scheduling
Experience with federal health or other regulated federal data programs
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