Senior Observability Platform Engineer

Nscale

7h•$160,000 - $230,000

About The Position

As a Senior Observability Platform Engineer, you’ll play a key role in designing, building, and scaling Nscale’s observability platform. You’ll focus on delivering reliable, high-quality visibility into GPU clusters, AI workloads, and the infrastructure that powers them. You approach observability as a product—balancing usability, scalability, and operational efficiency. You build systems that reduce cognitive load for engineers, surface meaningful signals, and enable fast, confident debugging when things go wrong. You’ll contribute to platform direction, implement critical systems, and collaborate closely with SRE, infrastructure, and AI/ML teams to ensure observability is embedded into everything we run. This is a hands-on engineering role with meaningful influence over platform design and evolution.

Requirements

5+ years in SRE, infrastructure engineering, platform engineering, or observability-focused roles
Experience operating and scaling observability systems in production environments
Strong understanding of monitoring concepts: metrics, logs, traces, alerting, and SLOs
Hands-on experience with several of: Prometheus, Thanos, VictoriaMetrics, Grafana, Loki, Tempo, OpenTelemetry, ClickHouse, Elastic
Solid programming skills (Python, Go, or similar) with the ability to build and maintain production systems
Experience working with Kubernetes-based infrastructure
Familiarity with Infrastructure-as-Code (Terraform, Ansible, or similar)
Pragmatic mindset with a focus on simplicity, reliability, and maintainability
Strong collaboration skills and ability to work across teams

Nice To Haves

Experience with observability data pipelines (Kafka, Vector, Fluent Bit, etc.)
Exposure to AI/ML infrastructure or GPU-based systems
Familiarity with performance monitoring for distributed systems
Experience improving developer experience through observability tooling

Responsibilities

Design, build, and operate scalable observability systems across metrics, logs, traces, and alerting
Contribute to architectural decisions around tooling, data pipelines, storage, and retention strategies
Improve signal quality by reducing noise, managing cardinality, and refining alerting practices
Help identify and address observability gaps before they impact reliability
Partner with SRE, infrastructure, and AI/ML teams to integrate observability into services and platforms
Develop reusable patterns, libraries, and best practices that improve consistency across teams
Participate in incident response and postmortems, driving actionable improvements
Evaluate and adopt tools that improve developer experience, scalability, and operational efficiency
Support and mentor engineers within the team through code reviews and knowledge sharing