Juvare is a SaaS software company focused on developing innovative enterprise resilience solutions for government agencies, corporations, healthcare providers, and higher education. Juvare solutions have supported over 500,000 emergency response incidents in all 50 states and 20 countries worldwide. Juvare helps our clients prepare, connect, and respond to protect people, property, and brands.
Role Overview
We are looking for a Sr. DevOps Engineer to help build, operate, and continuously improve the secure cloud platforms that power Juvare ’s mission-critical enterprise resilience solutions. In this role, you’ll partner across Engineering and Security to deliver reliable, scalable SaaS environments for commercial and federal customers , with a proven track record operating in regulated settings. Experience supporting AI/MLOps workflows is a plus.
Location
Must Have
- Cloud Platforms: Strong hands-on experience with AWS and Azure
- Regulated Environments: Experience operating in FedRAMP High, DoD Impact Level 5 (IL5), or equivalent regulated environments
- Compliance & ConMon: Strong understanding of Authority to Operate (ATO) processes, compliance, and continuous monitoring (ConMon)
- GovCloud: Experience working within AWS GovCloud or secure boundary environments
- Databases: Operational experience with managed databases (backup/restore, replication, performance, and access management; Azure SQL and Aurora PostgreSQL preferred)
- Infrastructure as Code: Experience with infrastructure as code (Terraform)
- CI/CD Pipelines: CI/CD pipeline experience (GitLab, GitHub)
- Automation (AI-Enabled): Experience building workflow automation and developer automation using tools like n8n, Replit, or similar
- Containers & Orchestration: Strong experience with containers and orchestration (Docker, Kubernetes, AKS, EKS, ECS/Fargate)
- Monitoring & Observability: Experience with monitoring and observability (Datadog, CloudWatch)
- Security Tooling: Exposure to security tooling (WAF, SIEM, vulnerability management)
- Scripting: Strong scripting skills (Python, Bash, Powershell)
- Production Operations: Experience in production operations (incident response, on-call, RCA)
- Architecture: Strong understanding of networking, security, and system architecture
- MLOps Pipelines: Experience with MLOps pipelines (training, deployment, monitoring)
- Tools: Familiarity with tools like SageMaker, MLflow, Kubeflow, or similar
- Model Deployment: Experience deploying models to production (real-time or batch)
- Data & Lifecycle: Understanding of data pipelines and model lifecycle management
Nice to Have
- Experience with LLMs / GenAI workflows (RAG, prompt engineering, fine-tuning)
- Familiarity with vector datab