Cloud & Infrastructure Manager
Griffin Global Systems
Herndon, VA · Posted October 10, 2026
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November 2026
- #2Best cities for pay after cost of living in Virginia$161k · of 15
- #3Best cities for pay after cost of living in the Southeast$161k · of 33
- #3Best all-round cities for AI careers in the Mid-Atlantic86 / 100 · of 37
- #4Best cities for pay after cost of living in the Mid-Atlantic$161k · of 37
- #4Best cities for software and engineering jobs in the Mid-Atlantic441 openings · of 68
- #4Best all-round cities for mid-career professionals in the Mid-Atlantic76 / 100 · of 37
Rankings about engineering jobs
- Best cities for software and engineering jobs #1 San Francisco (3,412 openings)
- Best cities for engineering pay after cost of living #1 San Mateo ($216k)
- Most requested AI skills in engineering jobs #1 AI tools in daily work (6.1%)
- AI tools named most often in engineering jobs #1 Claude (1.7%)
- Employers with the most engineering jobs #1 Amazon (2,992 roles)
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About the job
Required Qualifications
Leadership & Experience: 10+ years in Cloud, DevOps, Platform, or Data/ML Engineering, including 2+ years managing or leading engineers.
Infrastructure as Code (IaC): Expert, hands-on Terraform (modules, state management, multi-environment design).
Multi-Cloud Expertise: Deep hands-on experience with AWS and Azure (networking, IAM/RBAC, compute, security); familiarity with GCP. Proven cloud migration track record.
Containerization & GitOps: Hands-on Kubernetes (EKS, AKS) and ArgoCD or Flux.
CI/CD & Automation: Production GitHub Actions (or equivalent), Git workflows, and scripting (Python, Bash, or PowerShell).
Identity & OS: Enterprise SSO (Entra ID, SAML, OIDC, SCIM) and dual administration of Linux and Windows Server.
Cross-Domain Breadth: Ability to lead teams across DevOps, MLOps, and DataOps.
Communication & Modern Tooling: Strong communication for leadership alignment, team mentorship, and practical use of AI-assisted development tools.
Preferred Qualifications
MLOps & DataOps Tooling: Experience with MLflow, SageMaker, Azure ML, or DB change management (Liquibase/Atlas).
AI & Migration: Custom MCP server development and experience driving toolchain migrations (e.g., Azure DevOps to GitHub).
Databases & App Modernization: Azure SQL/Managed Instance experience and containerizing legacy applications (.NET/WebForms).
Certifications: AWS, Azure, or HashiCorp Terraform certifications.