Container Engineer

Accountabilities

• Platform reliability and operations: Define and maintain service-level indicators (SLIs), service-level objectives (SLOs), and error budgets for the container platform. Develop policies that connect reliability targets to platform changes and deployment decisions.

• Operational readiness and observability: Lead Operational Readiness Reviews (ORRs) for new capabilities and significant changes. Establish meaningful uptime metrics and improve visibility through comprehensive metrics, logs, and distributed traces across platform components.

• Incident management and continuous improvement: Participate in the team's on-call rotation, respond to platform incidents, and drive issues through resolution and follow-up. Facilitate blameless postmortems, identify recurring failure patterns, and implement lasting improvements that reduce detection and recovery times.

• Platform software engineering: Build, maintain, and deploy production-grade automation, controllers, operators, internal tools, and platform APIs. Develop custom solutions when existing tools do not adequately address the underlying technical challenges.

• Deployment automation and release management: Design and improve platform CI/CD pipelines, rollout mechanisms, and release processes that enable safe, efficient, and predictable deployments.

• Security and operational automation: Implement security automation covering intrusion detection, automated remediation, and patch management. Identify repetitive operational tasks and eliminate toil through reliable automation.

• Testing and quality assurance: Develop and maintain automated testing suites and pipelines that validate platform releases before they reach production workloads.

• Architecture and ecosystem development: Evaluate and evolve the container technology stack, including orchestration, runtimes, networking, workload isolation, and observability tools. Conduct failure-mode analysis, map dependencies, and design resilient architectures for multi-tenant environments.

• Infrastructure efficiency: Improve platform architecture to optimize infrastructure costs while maintaining appropriate standards for security, reliability, and performance across tenants.

• Engineering enablement: Help product teams adopt sustainable operational practices, including effective alerting, escalation procedures, runbook coverage, and reduced notification noise.

Requirements

• Professional experience: At least five years of experience in platform engineering, Kubernetes or container platform operations, Site Reliability Engineering (SRE), or production infrastructure, including operating production systems at scale and participating in on-call rotations.

• Deep technical expertise: Strong expertise in at least one of the following areas, ideally with experience across two:

  • Container tooling and ecosystem: In-depth knowledge of Kubernetes, containerd, OCI/CRI standards, and the broader Cloud Native Computing Foundation (CNCF) ecosystem. Familiarity with technologies such as Argo CD, Argo Rollouts, Cilium, eBPF, Gateway API, Karpenter, KEDA, gVisor, or Kata Containers is valuable.
  • Software engineering: Ability to write production-quality code in Go or a comparable systems programming language, build controllers and operators, and design platform APIs and custom automation solutions.
  • Operational excellence and SRE: Strong understanding of SLOs, error budgets, operational KPIs, incident response, blameless postmortems, and strategies for reducing mean time to detect (MTTD) and mean time to recover (MTTR).

• Multi-tenant infrastructure: Experience with large-scale, multi-tenant systems and an understanding of workload isolation mechanisms, including namespaces, role-based access control (RBAC), network policies, resource quotas, virtual clusters, and stronger isolation models such as VM-based runtimes.

• Cloud infrastructure: Confident working with AWS environments, including multiple accounts, IAM, and VPC networking.

• Infrastructure as code: Experience with infrastructure-as-code tools, preferably Pulumi, with Terraform or AWS CDK also suitable.

• Kubernetes proficiency: Practical experience deploying, operating, troubleshooting, and improving Kubernetes-based infrastructure.

• Automation mindset: A proactive approach to scripting and automating repetitive work to improve efficiency, reliability, and consistency.

• Communication and collaboration: Ability to explain complex technical concepts clearly to both infrastructure experts and product engineers, collaborate across disciplines, and work effectively in asynchronous, globally distributed teams.

• Adaptability and ownership: Comfort navigating ambiguity, making informed technical trade-offs, working independently, and continuously improving systems as requirements evolve.

Nice to have

• Experience building and operating a multi-tenant Kubernetes platform used by internal engineering teams.
• Familiarity with policy enforcement tools such as Kyverno or OPA/Gatekeeper.
• Experience with infrastructure cost attribution and optimization tools such as OpenCost or Kubecost.
• Knowledge of managed database platforms or PostgreSQL.
• Experience with observability technologies such as OpenTelemetry, Prometheus, VictoriaMetrics, and Grafana.
• A strong interest in open-source software and the cloud-native ecosystem.