DevOps Engineer

Vida Global is a publicly traded, early-stage AI company building an AI Agent Operating System that helps businesses manage AI workforces. They are seeking a DevOps Engineer to design, build, automate, and operate cloud systems that support their AI platform, ensuring reliability, security, and scalability.

Responsibilities:

• Designing and operating production AWS environments across VPC, EC2, EKS, ELB/NLB, Transit Gateway, Route 53, IAM, ACM, SSM, ECR, GuardDuty, and Secrets Manager
• Building secure multi-VPC networking patterns with hub-and-spoke architecture and route domain isolation
• Operating production EKS clusters, platform add-ons, autoscaling, RBAC, namespace boundaries, and upgrade workflows
• Managing infrastructure as code with Terraform, Terraform Cloud, reusable modules, and policy-controlled CI/CD authentication
• Building observability systems across Prometheus, Grafana, Alertmanager, kube-state-metrics, Node Exporter, and centralized monitoring patterns
• Implementing Kubernetes platform services through Helm, including load balancing, autoscaling, external secrets, metrics, and monitoring
• Improving platform security through private access patterns, least-privilege IAM, workload identity, SSM-only access, mTLS VPN, encrypted storage, and secure secret delivery
• Supporting AI/LLM infrastructure such as LiteLLM, model gateway telemetry, traffic control, autoscaling, and service-level monitoring
• Architect, operate, and improve AWS environments supporting Vida’s production platform
• Design secure networking patterns across VPCs, EKS clusters, private services, Transit Gateway, ELB/NLB, Route 53, and Global Accelerator
• Implement least-privilege IAM, workload identity through IRSA/OIDC, IMDSv2 enforcement, secure access controls, and production-ready AWS security patterns
• Use ACM, SSM, ECR, GuardDuty, Secrets Manager, and related AWS services to improve security, reliability, and operational efficiency
• Improve cross-region latency, traffic routing, and availability through Anycast, geo-routing, and resilient ingress patterns
• Build and maintain production infrastructure using Terraform, HCL, Terraform Cloud remote state, policy controls, and OIDC-based CI authentication
• Create and standardize reusable Terraform modules for networking, EKS, observability, security, and platform services
• Build reproducible AMIs with Packer, including hardened Docker and runtime dependencies
• Automate post-provisioning and configuration management with Ansible, dynamic EC2 inventory, SSM, Jinja2 templates, and multi-play orchestration
• Create deterministic Terraform-to-Ansible handoff patterns for infrastructure provisioning and application bootstrap
• Automate Helm lifecycle operations and environment-specific configuration rollout
• Deploy, operate, and upgrade Amazon EKS clusters using managed node groups and production-safe workflows
• Manage core EKS add-ons including VPC CNI, CoreDNS, kube-proxy, pod identity agent, metrics-server, external-secrets, cluster-autoscaler, aws-load-balancer-controller, and kube-prometheus-stack
• Implement autoscaling, RBAC boundaries, namespace segmentation, and Kubernetes CRDs such as ServiceMonitor, PodMonitor, ExternalSecret, and ClusterSecretStore
• Implement and operate Istio service mesh components, including base, control plane, ingress gateway, sidecar injection, and VirtualService routing policies
• Integrate Istio ingress with internal NLB patterns for private service exposure and service-to-service traffic governance
• Build and improve observability using Prometheus Operator, Grafana, Alertmanager, Node Exporter, kube-state-metrics, dashboards, and alerting standards
• Design federated monitoring patterns from in-cluster EKS workloads to centralized hub Prometheus infrastructure
• Integrate AI platform telemetry, including LiteLLM Prometheus callbacks, ServiceMonitor, model traffic visibility, latency tracking, and runtime anomaly detection
• Establish dashboards and alerts for cluster health, workload SLOs, infrastructure saturation, runtime errors, and service reliability
• Deploy and operate LiteLLM on Kubernetes using multi-replica architecture, HPA, Istio ingress, secure secret integration, and service-level monitoring
• Build scalable AI gateway patterns that support secure model access, traffic control, observability, and high availability
• Implement zero-trust infrastructure patterns including private EKS API endpoints, SSM-only operator access, and no public bastion exposure
• Enforce mTLS Client VPN with ACM-issued certificates and encrypted gp3 EBS volumes by default
• Integrate AWS Secrets Manager with External Secrets Operator for secure Kubernetes secret delivery
• Reduce operational risk through identity controls, segmentation, policy-driven access, secure defaults, and automated guardrails
• Partner with engineering to improve incident readiness, debugging workflows, runtime visibility, and production change safety

Requirements:

• 5+ years of experience in DevOps, infrastructure engineering, platform engineering, site reliability engineering, cloud engineering, or a related role
• Deep hands-on experience with AWS production environments, especially VPC, EC2, EKS, ELB/NLB, Transit Gateway, Route 53, IAM, ACM, SSM, ECR, GuardDuty, and Secrets Manager
• Strong experience with Terraform, Terraform Cloud, reusable modules, remote state, CI/CD authentication, and policy-controlled infrastructure workflows
• Strong Kubernetes and EKS experience, including managed node groups, core add-ons, Helm, RBAC, autoscaling, namespaces, and production upgrades
• Experience operating observability stacks with Prometheus, Grafana, Alertmanager, Node Exporter, kube-state-metrics, dashboards, and alerting
• Experience implementing security-first cloud patterns, including least-privilege IAM, IRSA/OIDC, IMDSv2, private access, encrypted storage, and secure secret management
• Comfort working with service mesh concepts and technologies such as Istio, ingress gateways, VirtualService routing, sidecar injection, and internal load balancer patterns
• Strong automation skills using HCL, YAML, Jinja2, Bash, Python, and infrastructure scripting
• Ability to troubleshoot complex distributed systems across cloud infrastructure, Kubernetes, networking, observability, and application runtime layers
• High ownership, strong judgment, and a bias toward automation, documentation, reliability, and secure defaults
• Comfort working in an early-stage company environment where priorities can change quickly and infrastructure work has direct customer impact
• Experience building or operating AI/LLM infrastructure, model gateways, LiteLLM, or similar AI platform services
• Experience with federated Prometheus architectures or centralized observability across multiple clusters and environments
• Experience with Packer-based AMI pipelines and hardened Linux images, especially Ubuntu ARM64
• Experience with hub-and-spoke AWS network architecture, Transit Gateway route domain isolation, Global Accelerator, Anycast, or geo-routing
• Experience with External Secrets Operator, AWS Secrets Manager, ClusterSecretStore, and Kubernetes-native secret delivery
• Experience supporting voice, communications, automation, telephony, reseller, or multi-tenant SaaS platforms
• Experience designing production readiness standards, SLOs, incident response practices, and operational runbooks
• Interest in AI agents, computer-use automation, and the infrastructure required to operate AI workforces at scale