About the role
Veeam is the Data and AI Trust Company, specializing in helping organizations ensure their data and AI are fully understood, secured, and resilient to enable the acceleration of safe AI at scale. As the market leader in both data resilience and data security posture management, Veeam is built for the convergence of identity, data, security, and AI risk. Headquartered in Seattle with offices in more than 30 countries, Veeam protects over 550,000 customers worldwide, who trust Veeam to keep their businesses running. Join us as we go fearlessly forward together, growing, learning, and making a real impact for some of the world’s biggest brands. Site Reliability Engineer — Government & Sovereign Cloud Veeam is building a global SRE function to support the Veeam Data Cloud, our SaaS platform. This role is part of
the team supporting our Government and Sovereign Cloud environment. Success here requires a self-starter mindset — you'll need to be comfortable building your own context and tracking down information across a large, distributed engineering organization. You'll work alongside senior engineers to execute on reliability work, close observability gaps, respond to incidents, and help maintain the operational foundation
the team runs on. What You Will Do Discovery & Documentation Get up to speed on VDC workloads, dependencies, and operational workflows by reading code, docs, and working with SMEs. Write and maintain runbooks, incident guides, and operational documentation. Support knowledge transfer and contribute to onboarding materials for
the team. Reliability & Incident Response Participate in incident response including triage, investigation, mitigation, and postmortems. Help implement and maintain SLIs, SLOs, and error budgets defined by
the team. Identify reliability issues during incidents or reviews and propose concrete improvements. Support high availability and fault tolerance work on Azure, including Azure Government. Observability Close monitoring gaps by implementing instrumentation, alerting, and dashboards based on team standards. Contribute to toil reduction through automation and tooling improvements. Participate in on-call rotations. Infrastructure & Delivery Work with IaC , CI/CD pipelines, and deployment tooling in compliance-restricted environments. Support testing, canary deployments, and release validation workflows. Implement changes to infrastructure and configuration following established patterns and review processes. Collaboration Work with engineering, security, compliance, and operations teams to execute on reliability improvements. Communicate clearly about system behavior, risk, and status — in writing and in meetings. Raise blockers and gaps proactively; don't wait for problems to escalate. What We Are Looking For Required 3+ years in Software Engineering, with at least 1 year in SRE, Platform Engineering, or DevOps working on cloud-hosted services. Experience with cloud infrastructure on Azure or a comparable cloud provider. Familiarity with regulated or compliance-oriented environments such as government (FedRAMP, CMMC ), financial (PCI-DSS), or healthcare ( HIPAA ). You understand that compliance shapes what you can and can't do operationally. Able to read and understand code well enough to investigate system behavior without always having someone walk you through it. Experience with monitoring and observability tools (e.g., Prometheus, Grafana, OpenTelemetry, ELK stack). Experience with IaC tools (Terraform, Terragrunt, or Pulumi) and container orchestration (Kubernetes). Experience with CI/CD tooling such as GitHub Actions, Azure DevOps, GitLab CI, or ArgoCD. Strong programming skills in one or more of: TypeScript/ JS , Go, Java, C#, or similar. Solid understanding of distributed systems fundamentals and networking basics. Clear written and verbal communication skills. Preferred Experience in Government or Sovereign Cloud environments (e.g., Azure Government, AWS GovCloud). Background in SaaS platforms or multi-tenant systems. Familiarity with chaos engineering, resilience testing, or load testing. Exposure to building or improving reliability practices on a team. Familiar with AI-first development workflows using LLM-powered tools for automation, code generation, or documentation.
