Cerebras

9 months ago

Principal Engineer, Inference Cloud

✓ Verified Job

Canonical indexed version, validated from employer's careers page.

Source: Company careers pageValidated by: Fursa AI

Last checked: 3 hours agoStatus: Live

Job Summary

Own the Inference Cloud Platform, the cloud layer behind an AI inference service. Drive long-term architecture and direction across multi-region topology, failure domains, and service boundaries. Build and evolve highly reliable, latency-sensitive systems with active-active patterns, graceful degradation, and clear SLOs. Contribute production code on critical paths, lead difficult production issues, and mentor teams through design reviews, standards, and operational rigor.

Location: Sunnyvale

Workplace: Onsite

Employment Type: Full time

Job Function: Communications, PR & Community

Seniority: Mid level

Key Responsibilities

•Define and prioritize the most important platform problems, making tradeoffs on what the platform will and won’t support.
•Set the long-term technical direction for the Inference Cloud Platform, including multi-region topology, failure domains, and service boundaries.
•Architect reliability and performance improvements using active-active designs, rapid failover, and graceful degradation with clear SLOs.
•Contribute production code on critical paths and perform design reviews, making build-vs-buy and other architectural decisions.
•Lead hardest production issues and drive observability, incident response, capacity planning, and post-incident improvements across systems.

Key Requirements

•10+ years of software engineering experience building and operating large-scale distributed systems or cloud infrastructure.
•Deep expertise in distributed systems architecture in cloud environments, including networking, compute orchestration, container platforms, and multi-region production services.
•Proven architectural judgment for highly available, latency-sensitive systems at scale.
•Experience optimizing latency, throughput, and efficiency in high-QPS systems, including TTFT and tail-latency reduction.
•Strong backend/systems proficiency in Go, C++, or Python, with the ability to contribute production code directly.

Experience:10+ yearsDistributed systemsCloud infrastructureAI inferenceModel serving

Skills:Technical credibilityCommunicationJudgmentMentorshipOperational rigor

Tech Stack:GoC++PythonDistributed systemsCloud infrastructureNetworkingCompute orchestrationContainer platformsMulti-regionActive-active systemsCircuit breakingBackpressureLoad sheddingObservabilityMetricsLoggingTracingAlertingSLISLO

Company Brief

Cerebras

Designs and builds wafer-scale AI accelerators and systems for large-scale deep learning workloads, delivering specialized hardware and software to accelerate model training and inference for enterprises and research institutions.

Industry: Hardware Devices

Company Size: Large (251 to 1,000 employees)

Growth: Scaleup

Headquarters: Sunnyvale, United States

Founded: 2016

Website LinkedIn

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Cerebras

9 months ago

Principal Engineer, Inference Cloud

✓ Verified Job

Canonical indexed version, validated from employer's careers page.

Source: Company careers pageValidated by: Fursa AI

Last checked: 3 hours agoStatus: Live

Job Summary

Location: Sunnyvale

Workplace: Onsite

Employment Type: Full time

Job Function: Communications, PR & Community

Seniority: Mid level

Key Responsibilities

•Define and prioritize the most important platform problems, making tradeoffs on what the platform will and won’t support.
•Set the long-term technical direction for the Inference Cloud Platform, including multi-region topology, failure domains, and service boundaries.
•Architect reliability and performance improvements using active-active designs, rapid failover, and graceful degradation with clear SLOs.
•Contribute production code on critical paths and perform design reviews, making build-vs-buy and other architectural decisions.
•Lead hardest production issues and drive observability, incident response, capacity planning, and post-incident improvements across systems.

Key Requirements

•10+ years of software engineering experience building and operating large-scale distributed systems or cloud infrastructure.
•Deep expertise in distributed systems architecture in cloud environments, including networking, compute orchestration, container platforms, and multi-region production services.
•Proven architectural judgment for highly available, latency-sensitive systems at scale.
•Experience optimizing latency, throughput, and efficiency in high-QPS systems, including TTFT and tail-latency reduction.
•Strong backend/systems proficiency in Go, C++, or Python, with the ability to contribute production code directly.

Experience:10+ yearsDistributed systemsCloud infrastructureAI inferenceModel serving

Skills:Technical credibilityCommunicationJudgmentMentorshipOperational rigor

Company Brief

Cerebras

Industry: Hardware Devices

Company Size: Large (251 to 1,000 employees)

Growth: Scaleup

Headquarters: Sunnyvale, United States

Founded: 2016

Website LinkedIn