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About Command|Link
Command|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, maximise uptime and improve the bottom line.
Learn more about us here!
This is a 100% remote position.
About 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 general customer base.
Your mandate: keep the platform fast, available, and scalable as CommandLink grows — enabling fast, iterative deployments without sacrificing uptime.
You will 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 judgement 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 post-mortems, as well as building the automation that makes on-call sustainable long-term.
You will 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 post-mortems




Kubernetes cluster operations: manage HA multi-node and cloud clusters in production, handle rolling upgrades, resource quotas, autoscaling, network policies, and pod disruption budgets
Distributed 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 tuning
Temporal workflow platform: maintain and scale Temporal server deployments; work with engineering to design workflows for durability and back-pressure
Azure/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 environments
Observability: build and maintain a comprehensive observability stack, metrics, logs, traces, and dashboards that give engineers actionable signals rather than noise
Security and compliance: work with the security team to harden infrastructure, enforce least-privilege policies, and support compliance requirements
Capacity planning: proactively model growth, identify bottlenecks before they become incidents, and lead scaling initiatives for critical components
Takes on additional responsibilities and projects as needed to support the success of the team and organization.
Essential
What you'll need for success:
6+ years in a Site Reliability Engineering, DevOps, or Platform Engineering role in a production environment
Deep, hands-on Kubernetes experience: cluster administration, HA configurations, networking (CNI, ingress, service mesh), and storage not just application deployment
Proven experience operating Apache Kafka at scale: topic management, consumer group tuning, broker operations, and monitoring lag




Experience with Apache Flink or equivalent stream processing frameworks in production
OpenSearch / Elasticsearch cluster operations: index management, scaling strategies, performance tuning, and snapshot management
Azure/AWS/GCP cloud platform expertise: AKS, virtual networking, managed identities, monitoring, and cost management
Solid understanding of distributed systems theory: CAP theorem, consensus protocols, failure modes, back-pressure, and circuit breaking
Infrastructure as Code mindset — Terraform, Helm, or equivalent
Temporal 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 operating high-availability architectures across multiple availability zones or regions
Nice To Have
Experience with Vector (from Datadog) for log and metric collection and routing pipelines
Datadog for APM, infrastructure monitoring, log management, or dashboards
Experience with service meshes (Istio, Linkerd, or Cilium)
Familiarity with chaos engineering practices (Chaos Monkey, LitmusChaos, or similar)
Contributions to open source infrastructure tooling
Experience working in or with network/telco SaaS products
Knowledge of eBPF-based networking or observability tools
Why you'll love life at Command|Link
Room to grow at a high-growth company
An environment that celebrates ideas and innovation
Your work will have a tangible impact
Flexible time off
Fun events at cool locations
Employee referral bonuses to encourage the addition of great new people to the team
At CommandLink, we're committed to creating a fair, consistent, and efficient hiring experience.
As part of our process, we use AI-assisted tools to help review and analyze applications.
These tools support our recruiting team by identifying qualifications and experience that align with the requirements of each role.
AI tools are used only to assist in the evaluation process — they do not make final hiring decisions.
Every application is reviewed by a member of our recruiting or hiring team before any decisions are made.
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📌 Devops Engineer (Godoy Cruz)
🏢 CommandLink
📍 Godoy Cruz