Principal Engineer, Inference Cloud
Remote • Sunnyvale, CA • FullTime
Posted 1y ago
Job Location
Sunnyvale, CA
Tech Stack
Remote Work Policy
Fully remote
Employment Type
FullTime
Categories
AI Infrastructure Engineer
About the job
Cerebras Systems is seeking a Principal Engineer for its Inference Cloud Platform team. This senior role is responsible for the cloud layer that powers the Inference Service, focusing on availability, latency, reliability, and multi-region scalability. The ideal candidate will identify high-leverage platform challenges, define long-term architecture, and contribute production code to critical paths. This position requires framing ambiguous problems, making trade-offs, and driving execution without a clear specification. The scope includes multi-region traffic architecture, graceful degradation under bursty AI workloads, high-QPS performance, and maintaining a fast, available platform under changing demand, in close partnership with ML, Product, and Infrastructure teams.
Responsibilities
- Identify and prioritize the most important technical problems for the platform, making explicit trade-off decisions.
- Set the long-term technical direction for the Inference Cloud Platform, including multi-region topology and system evolution.
- Architect active-active systems with rapid failover and graceful degradation, driving improvements in latency, throughput, and resilience.
- Contribute production code to critical paths, review designs and implementations, and make architectural decisions.
- Lead on complex production issues and cross-system bottlenecks, driving observability, incident response, and capacity planning.
- Drive platform-wide decisions across adjacent teams on reliability, API design, and deployment strategy.
- Mentor other engineers by raising the quality of technical decision-making through design feedback and setting engineering standards.
Requirements
- 10+ years of experience in software engineering with substantial 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.
- Strong track record of making sound architectural decisions for highly available, latency-sensitive systems at scale.
- Experience optimizing latency, throughput, and efficiency in high-QPS systems; TTFT and tail-latency reduction experience is a plus.
- Strong proficiency in backend or systems languages such as Go, C++, or Python.
- Experience designing observability and reliability practices, including metrics, logging, tracing, alerting, incident response, and SLI/SLO/SLA-driven operations.
- Ability to influence senior engineers and cross-functional partners through technical credibility and communication.
- Experience with ML inference infrastructure, model serving systems, or GPU-accelerated workloads is a plus.
Benefits
- 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.
- Job stability with startup vitality.
- Simple, non-corporate work culture that respects individual beliefs.