Sr. DevOps Engineer (REMOTE)

Role overview

Build and operate the cloud infrastructure and release systems behind a cybersecurity product, supporting both commercial services and government workloads. The role focuses on secure, reliable delivery across AWS and AWS GovCloud, including regulated environments and infrastructure for AI features.

Responsibilities

- Build and maintain CI/CD pipelines and Kubernetes deployments, using tools such as Helm and GitOps workflows to promote releases across environments. - Provision and manage infrastructure as code, and support both cloud and on-premise deployments. - Maintain environment separation, access controls, secrets, and continuous compliance for government authorization boundaries. - Improve monitoring, logging, alerting, and operational automation; participate in incident response and root-cause analysis. - Coordinate database releases and schema migrations, and troubleshoot application and deployment issues with engineering teams. - Support secure infrastructure for AI services, reviewing data flows and third-party model use with security and compliance partners.

Requirements

- Hands-on experience operating AWS infrastructure and Kubernetes workloads in production. - Experience designing and maintaining CI/CD pipelines and infrastructure as code, such as Terraform, CloudFormation, or CDK. - Knowledge of cloud security practices, including access management, secrets handling, network segmentation, and compliance controls. - Familiarity with monitoring and incident response, and the ability to investigate application and infrastructure issues. - Experience with database deployment or schema migration workflows; PostgreSQL and migration tooling are relevant examples. - Ability to work across engineering and security teams and document operational work clearly.

Nice to have

- Experience with AWS GovCloud or regulated frameworks such as FedRAMP, GovRAMP, IL5, or NIST 800-53. - Experience with Helm, ArgoCD, GitHub Actions, Jenkins, Bitbucket Pipelines, or comparable tools. - Support for production LLM services, inference workloads, LLMOps, vector databases, or retrieval systems; familiarity with AI security risks is useful. - AWS certifications, container security scanning, software supply-chain security, or cybersecurity product experience.

Benefits and work setup

The position is listed as remote in the United States, with regional office work also mentioned. Benefits include paid time off, holidays, retirement plans, insurance, and professional development opportunities.