Staff Software Engineer - Observability

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. This website or its third-party tools process personal data. For more details, click here to review our CCPA disclosure notice.