DevOps Engineer

About Command|LinkCommand|Link is a global SaaS Platform providing network, voice services, and IT security solutions, helping corporations consolidate their core infrastructure into a single vendor and layering on a proprietary single pane of glass platform. Command|Link has revolutionized the IT industry by tackling the problems our competitors create. In recognition for our unprecedented innovation and dedication, Command|Link was recognized as the SD-WAN Product of the Year, ITSM Visionary Spotlight, UCaaS Product of the Year, NaaS Product of the Year, Supplier of the Year, and the AT&T Strategic Growth Partner. Command|Link has built the only IT platform for scale that solves ISP vendor sprawl and IT headaches. We make it easy for our customers to get more done, maximize uptime and improve the bottom line.Learn more about us here!This is a 100% remote positionAbout your new role:As our Founding DevOps Engineer, you will own the reliability of a high-throughput distributed platform processing network telemetry, voice, and security data for a global customer base. Your mandate: keep the platform fast, available, and scalable as CommandLink grows — enabling fast, iterative deployments without sacrificing uptime.You'll work hands-on across VMs, firewalls, Kubernetes clusters, Kafka and Flink pipelines, OpenSearch, and Azure infrastructure — designing systems to fail gracefully and recover automatically, not just monitoring them. You'll bring strong platform judgment to decisions that directly impact customer uptime, data latency, and our ability to scale new product lines without rearchitecting from scratch.Working closely with Engineering and Product leaders, you'll embed reliability into how we build. That means driving SLO definition, incident response, and postmortems, as well as building the automation that makes on-call sustainable long-term.You'll also lead a genuine greenfield initiative: transforming our infrastructure into a fully code-defined Infrastructure as Code model — bringing consistency, repeatability, and engineering rigor to how we provision, manage, and evolve the platform.Key Responsibilities:Own platform reliability end-to-end: define and enforce SLOs/SLIs, build alerting strategies, lead incident response, and drive blameless postmortemsKubernetes cluster operations: manage HA multi-node and cloud clusters in production, handle rolling upgrades, resource quotas, autoscaling, network policies, and pod disruption budgetsDistributed data infrastructure: operate and scale Kafka clusters, Flink streaming jobs, and OpenSearch clusters under sustained high-throughput workloads, including rebalancing, partition management, index lifecycle policies, and shard tuningTemporal workflow platform: maintain and scale Temporal server deployments; work with engineering to design workflows for durability and backpressureAzure/AWS/GCP infrastructure: manage and optimise Azure/GCP/AWS environments including K8S, Networking, Monitoring, Vaults, and IAM; contribute to IaC codebase (Terraform or Bicep)CI/CD and deployment pipelines: improve build, release, and deployment pipelines to enable safe, fast, and automated delivery across environmentsObservability: build and maintain a comprehensive observability stack, metrics, logs, traces, and dashboards that give engineers actionable signals rather than noiseSecurity and compliance: work with the security team to harden infrastructure, enforce least-privilege policies, and support compliance requirementsCapacity planning: proactively model growth, identify bottlenecks before they become incidents, and lead scaling initiatives for critical componentsTakes on additional responsibilities and projects as needed to support the success of the team and organization.What you'll need for success:Essential:6+ years in a Site Reliability Engineering, DevOps, or Platform Engineering role in a production environmentDeep, hands-on Kubernetes experience: cluster administration, HA configurations, networking (CNI, ingress, service mesh), and storage not just application deploymentProven experience operating Apache Kafka at scale: topic management, consumer group tuning, broker operations, and monitoring lagExperience with Apache Flink or equivalent stream processing frameworks in productionOpenSearch / Elasticsearch cluster operations: index management, scaling strategies, performance tuning, and snapshot managementAzure/AWS/GCP cloud platform expertise: AKS, virtual networking, managed identities, monitoring, and cost managementSolid understanding of distributed systems theory: CAP theorem, consensus protocols, failure modes, backpressure, and circuit breakingInfrastructure as Code mindset — Terraform, Helm, or equivalentTemporal workflow engine: deployment, operation, and scaling (or strong experience with an equivalent durable execution platform such as Cadence or Conductor)Strong scripting and automation skills (Bash, PHP, Python, or Go) Experience designing and operati