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Senior DevOps Engineer at Aldea. Why This Role Matters. We're building AI infrastructure that scales. With 5 distinct environments managing complex multi-cluster Kubernetes deployments, we need infrastructure experts who can architect systems for production readiness while maintaining security and operational excellence. This isn't just maintaining servers—you'll be designing the backbone that powers our AI platform across development, staging, and production environments.. What You'll Own. Multi-Environment Kubernetes Architecture. . Manage 5 distinct environments (NMS, Sandbox, Development, Staging, Production) with different security and access requirements. . Design redundancy and failover mechanisms for our centralized NMS hub that manages all environments. . Infrastructure as Code Excellence. . Develop and maintain Pulumi-based infrastructure using Python. . Manage complex cross-environment dependencies and VPC peering relationships. . Automate resource provisioning and configuration management. . Zero-Trust Security Implementation. . Implement and maintain certificate-based VPN access with internal DNS resolution. . Configure WAF, security groups, and network policies for VPN-only access. . Manage HashiCorp Vault integration for secure credential management across environments. . Comprehensive Observability. . Deploy and configure Prometheus, Grafana, Loki, Jaeger, and CloudWatch. . Implement unified monitoring across distributed infrastructure. . Design alerting and incident response procedures. . API Platform Management. . Deploy and maintain the centralized API that manages all environments from the NMS hub. . Implement automation for managing training jobs and inference across multiple Kubernetes clusters. . Optimize GPU and CPU resource utilization across node groups. . Must-Have Requirements. Experience & Technical Depth. . 5+ years in DevOps, SRE, or infrastructure engineering. . Expert-level Kubernetes experience with EKS and multi-cluster management. . Strong Python programming skills for infrastructure automation and API development. . Infrastructure & Cloud Expertise. . Infrastructure as Code expertise with Pulumi, Terraform, or similar tools. . Deep AWS knowledge: VPC, EKS, ECR, S3, CloudWatch, IAM, and networking. . Linux system administration and containerization with Docker. . Monitoring & Security. . Hands-on experience with Prometheus, Grafana, and centralized logging systems. . Network security experience including VPN, firewalls, and certificate management. . Understanding of zero-trust architecture principles. . Nice-to-Have Qualifications. . Machine Learning infrastructure experience (GPU clusters, model serving, ML pipelines). . HashiCorp Vault administration and integration. . GitOps experience with ArgoCD or similar tools. . Service mesh experience (Istio, Linkerd). . Database administration (PostgreSQL, Redis, Elasticsearch). . CI/CD pipeline design and multi-cloud infrastructure experience. . 90-Day Success Metrics. Infrastructure Stability. . Zero unplanned downtime across production environments. . Successfully implement disaster recovery procedures with tested failover mechanisms. . Achieve 99.9% uptime SLA across all critical services. . Security & Compliance. . Complete VPN-only access implementation with certificate-based authentication. . Successfully integrate HashiCorp Vault across all environments. . Pass security audit with comprehensive logging and monitoring in place. . Operational Excellence. . Reduce infrastructure provisioning time by 50% through automation. . Implement comprehensive monitoring with <5 minute mean time to detection. . Optimize GPU utilization rates above 80% across training workloads. . Key Challenges You'll Solve. Architectural Complexity. . The NMS hub is a single point of failure—you'll architect redundancy without compromising centralized management. . Balance VPN-only security requirements with operational efficiency for remote team access. . Manage complex service discovery across 5 interconnected environments. . Scale & Performance. . Optimize GPU resources across competing training and inference workloads. . Implement cost optimization strategies while maintaining performance requirements. . Design monitoring systems that scale with our infrastructure growth. . Company Location: United States.