Staff Software Engineer - Observability

We’re looking for a Software Engineer focused on Observability to build and evolve the systems that give us deep visibility into large-scale, performance-critical production systems.

You’ll design and implement metrics, logging, tracing, and alerting infrastructure that enables fast debugging, high reliability, and confident operation of complex distributed systems. This role sits at the intersection of platform engineering, distributed systems, and reliability.

This is not a dashboards-only role — you’ll be writing production software, shaping internal platforms, and working closely with engineers across the stack.

Responsibilities

Design and implement observability instrumentation across services and platforms

Build and maintain telemetry pipelines for metrics, logs, and traces at scale

Develop internal observability platforms, libraries, and tooling

Define and operationalize SLIs, SLOs, and alerting strategies

Partner with engineers to make systems debuggable by design

Reduce MTTR by enabling fast root-cause analysis during incidents

Create clear, actionable dashboards and alerts that reflect real system health

Balance telemetry signal vs cost, noise, and performance impact

Improve the developer experience around observability and debugging

Qualifications:

Core Engineering Skills

Strong experience in backend or systems software engineering

Proficiency in one or more of:

Go, C++, Rust, Java, Python

Solid understanding of:

Distributed systems

Networking fundamentals

Concurrency and performance tradeoffs

Observability & Reliability Experience

Hands-on experience with:

Metrics, logs, and distributed tracing

Production monitoring and alerting

Familiarity with tools such as:

OpenTelemetry

Prometheus

Grafana

Datadog / Elastic / Jaeger / Tempo (or similar)

Experience designing:

High-signal alerts

Scalable telemetry pipelines

Service-level indicators and objectives

Preferred Qualifications:

Experience in high-performance computing, AI/ML systems, or inference platforms

Hardware-aware observability (accelerators, GPUs, custom hardware)

Prior SRE or platform engineering background

Experience debugging large-scale production incidents

Building internal developer platforms or shared libraries

Why Join Cerebras

People who are serious about software make their own hardware. At Cerebras, we have built a breakthrough architecture that is unlocking new opportunities for the AI industry. With dozens of model releases and rapid growth, we’ve reached an inflection point in our business. Members of our team tell us there are five main reasons they joined Cerebras:

Build a breakthrough AI platform beyond the constraints of the GPU.

Publish and open source their cutting-edge AI research.

Work on one of the fastest AI supercomputers in the world.

Enjoy job stability with startup vitality.

Our simple, non-corporate work culture that respects individual beliefs.

Find out more about what it's like to work at Cerebras here!

Apply today and become part of the forefront of groundbreaking advancements in AI!

Cerebras Systems is committed to creating an equal and diverse environment and is proud to be an equal opportunity employer. We celebrate different backgrounds, perspectives, and skills. We believe inclusive teams build better products and companies. We try every day to build a work environment that empowers people to do their best work through continuous learning, growth and support of those around them.

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