Observability Platform Engineer

Mirantis

Observability Platform Engineer building metrics, logging, tracing, and alerting platforms for Mirantis’s Kubernetes-native AI infrastructure. Improving incident detection and resolution across globally distributed compute environments.

Posted 8/21/2026full-timeRemote • 🇰🇿 KazakhstanMid-LevelSeniorWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in designing and building observability platforms for large-scale production environments, with a strong focus on metrics, logging, and distributed tracing. Proficient in implementing SLO/SLI frameworks and integrating observability tooling with incident management workflows.

Highest-signal resume keywords

Observability Platform DesignMetrics, Logging, Distributed TracingSLO/SLI Framework ImplementationHigh-Volume Telemetry PipelinesKubernetes and Cloud-Native Infrastructure

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

GoPythonRustPrometheusGrafanaOpenTelemetryLokiElasticsearchJaegerEBPF

Soft Skills

Strong Communication SkillsAbility to Work in Fast-Moving Environment

Tools & Technologies

ThanosCortexMimirAIOpsAutomated Triage Systems

Industry Keywords

High-Performance ComputeManaged ServicesOpen-Source ContributionsIncident Management WorkflowsRoot-Cause Analysis

Tech Stack

Tools & technologies

CloudElasticSearchGoGrafanaKubernetesPrometheusPythonRust

About the role

Key responsibilities & impact

Design, build, and operate metrics, logging, distributed tracing, and alerting platform components
Build high-volume, high-cardinality telemetry pipelines for large infrastructure fleets
Define and implement SLO/SLI frameworks and alerting strategies
Partner with service delivery and operations teams to build incident-focused observability
Integrate observability tooling with incident management workflows, root-cause analysis, and post-incident reviews
Improve detection speed and reduce MTTD and MTTR
Contribute to AI-assisted operations tooling, including automated triage, anomaly detection, and engineer-assist tools
Own the reliability, scalability, and security of the observability stack
Document architecture, runbooks, and operational practices

Requirements

What you’ll need

Proven experience designing and building observability platforms for large-scale, production infrastructure environments
Strong hands-on experience with metrics, logging, and distributed tracing tooling, such as Prometheus, Grafana, OpenTelemetry, Loki, Thanos/Cortex/Mimir, Elasticsearch/OpenSearch, and Jaeger/Tempo, or equivalents
Experience with high-volume telemetry pipelines and tradeoffs involving cardinality, retention, cost, and query latency
Strong software engineering skills in at least one relevant language, such as Go, Python, or Rust
Experience with Kubernetes and cloud-native infrastructure
Solid understanding of SLO/SLI/error-budget practices and low-noise alerting design
Comfortable working in a fast-moving environment
Strong communication skills and ability to work directly with operations/service delivery teams
Preferred: observability for GPU/HPC or specialized high-performance compute environments
Preferred: eBPF-based observability tooling
Preferred: AIOps/ML-based anomaly detection or automated triage systems
Preferred: managed services or MSP context
Preferred: contributions to open-source observability projects

Benefits

Comp & perks

Professional development and training
Attend conferences and working groups
Company outings, happy hours, hackathons, and tech talks
Competitive compensation package with a strong benefits plan
Remote work arrangement