Senior Observability Platform Engineer for AI GPU Cloud

Greenhouse Software, Inc.; Northern (KY); Hybrid; USD 160,000 - 230,000; Full time

Benefits offered by this job

Medical

Dental

Vision

Flexible PTO

Parental Leave

Retirement Plan

Job summary

Nscale is hiring a Senior Observability Platform Engineer to design, build, and scale our observability stack for GPU-driven AI workloads. You’ll partner with SRE, infra, and AI/ML teams to deliver reliable visibility across clusters and workloads, balancing usability, reliability, and performance.

This hands-on role involves creating reusable patterns, contributing to platform direction, and mentoring engineers while embedding observability into every service we run.

Qualifications

• 5+ years in SRE, infrastructure engineering or observability roles.
• Experience operating observability systems in production environments.
• Strong monitoring concepts and production reliability focus.

Responsibilities

• Design, build, and operate scalable observability systems across metrics, logs, traces, and alerting.
• Collaborate with SRE, infra, and AI/ML teams to embed observability into services.
• Improve signal quality, reduce noise, and refine alerting practices.
• Address observability gaps before impact, and drive postmortems improvements.
• Develop reusable patterns and best practices for teams to follow.
• Participate in incident response and remediation actions.
• Evaluate tools to improve developer experience and scalability.
• Mentor engineers through code reviews and knowledge sharing.

Skills

SRE Experience

Production systems

Collaboration

Observability concepts

Python

Go

Tools

Prometheus

Thanos

VictoriaMetrics

Grafana

Loki

Tempo

OpenTelemetry

ClickHouse

Elastic

Kubernetes

Terraform

Ansible

Job description

Nscale is hiring a Senior Observability Platform Engineer to design, build, and scale our observability stack for GPU-driven AI workloads. You’ll partner with SRE, infra, and AI/ML teams to deliver reliable visibility across clusters and workloads, balancing usability, reliability, and performance.

This hands-on role involves creating reusable patterns, contributing to platform direction, and mentoring engineers while embedding observability into every service we run.