Staff Software Engineer - Observability
AI in this role
Cerebras Systems builds the world's largest AI chip, 56 times larger than GPUs. This architecture allows Cerebras to deliver industry-leading training and inference speeds; over 10 times faster than GPU-based hyperscale cloud inference services.
This order of magnitude increase in speed is transforming the user experience of AI applications, unlocking real-time iteration and increasing intelligence via additional agentic computation.
Cerebras works with the leading model labs, global enterprises, and cutting-edge AI-native startups. OpenAI recently announced a multi-year partnership with Cerebras, to deploy 750 megawatts of scale, transforming key workloads with ultra high-speed inference.
About the team
The Cerebras Inference team’s mission is to deliver the world’s most performant, secure, and reliable enterprise-grade AI service. We build and operate large-scale distributed systems that power AI inference at unprecedented speed and efficiency. Join us to help scale inference and accelerate AI.
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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How we rate this
Staff Software Engineer - Observability at Cerebras rates 87 out of 100 for how much of the daily work is AI. That makes it Builds AI (AI Level 4 of 4). The level is about AI in the job, not seniority.
Builds AI. The job is building AI systems.
- ●●●● Builds AI80 to 100
- ●●●○ Works on AI60 to 79
- ●●○○ Uses AI40 to 59
- ●○○○ Little AI0 to 39
Levels come from how often the tools, models and workflows of the role are named in the posting itself. Open the description and count.
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- Tell me about a research question you investigated. What did you find?
- Walk me through how you've used OpenAI in your day-to-day work.
- How would you decide a model or AI system is ready to ship?
- Tell me about a time a model underperformed in production. How did you find out, and what did you change?
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- List these exact terms on your resume: AI Research and OpenAI. An applicant tracking system matches the wording, not the idea.
- Attach one line of real, concrete experience to at least one of them — a tool named with nothing behind it rarely survives a human read.
- Lead with what you built, trained or shipped — this role is judged on the AI system itself, not the tools around it.
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