Devops Engineer

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 global 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.