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Cerebras

AI accelerator hardware replacing GPUs

Staff Software Engineer - Observability

Backend EngineeringConfirmed live in the last 24 hours
Full-timeSunnyvale, CA, USANo salary listedHybrid

About the Job

Requirements

  • At least 8 years of software engineering experience, including at least 4 years building or operating observability or monitoring platforms at significant scale, such as millions of active time series or petabytes of log data.
  • Deep expertise in the open-source observability ecosystem, including operating, tuning, and extending systems such as Prometheus, Thanos, Cortex, Mimir, Elasticsearch, ClickHouse, or Loki, and understanding their internals, failure modes, and cost characteristics.
  • Experience using OpenTelemetry for instrumentation across a polyglot services environment.
  • Strong experience in Python; proficiency in Go is preferred.
  • Strong distributed systems and Kubernetes expertise, including sharding, replication, consistency models, monitoring Kubernetes and its workloads, and understanding tradeoffs in reliable data pipelines at scale.
  • Experience with observability cost management and capacity planning at scale.
  • Track record of setting technical direction and driving adoption across multiple teams.
  • Ability to operate effectively with ambiguity and translate business needs into technical strategy.

Responsibilities

  • Own the long-term architecture and roadmap for the observability platform across metrics, logs, traces, and events; drive adoption across the engineering organization through RFCs, design reviews, and close partnership with stakeholders.
  • Design telemetry pipelines that handle high-cardinality, high-frequency data from thousands of Wafer-Scale Engines, large Kubernetes clusters, and the connecting storage and networking fabric; solve ingestion and query performance problems beyond conventional approaches.
  • Partner with Engineering, SRE, Hardware, and ML Infrastructure teams to define SLOs, build alerting strategies, and create tooling that accelerates root cause analysis and reduces MTTR; make system health and failure diagnosis accessible to engineers.
  • Work with engineering teams across the stack to surface critical hardware health signals in a unified observability layer alongside software metrics.
  • Design and implement instrumentation libraries and standards using OpenTelemetry so rich observability is the default for every service; establish conventions that scale across teams.
  • Mentor senior engineers, raise the technical bar across the organization, influence engineering practices across team boundaries, and foster a culture of operational excellence.

Desired Qualifications

  • Proficiency in Go.

About the Company

Cerebras

AI accelerator hardware replacing GPUs

Cerebras Systems creates AI acceleration hardware and software. Its CS-2 system is designed to replace traditional GPU clusters for AI workloads, speeding up training and inference while simplifying the setup by eliminating the need for parallel programming, distributed training, and cluster management. The product works as a single, large processor-based accelerator with accompanying software and cloud services to run AI models efficiently, reducing latency and time to results. Compared with competitors, Cerebras differentiates itself with the largest processor in the industry and an integrated hardware-software stack that aims to streamline AI workflows rather than relying on multi-GPU clusters. The company's goal is to help research labs, healthcare, finance, and other industries achieve faster, more cost-effective AI development and deployment by offering a turnkey high-performance AI compute solution.

Company size
501-1,000
Company stage
IPO
Headquarters
Sunnyvale, CA
Founded
2016

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