The opportunity
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.
What you'll do
Problem Definition & Prioritization. Identify the most important technical: problems for the platform, often before there's a clear ask. Make explicit tradeoff decisions about what the platform will and won't support, with reasoning that holds up under scrutiny from senior engineering leadership.
Platform Direction . Set the long-term technical direction for the Inference: Cloud Platform, including multi-region topology, failure domains, service boundaries, and system evolution over time.
Reliability & Performance. Architect active-active systems with rapid: failover and graceful degradation (circuit breaking, backpressure, load shedding) with clear SLOs. Drive improvements in latency, throughput, capacity efficiency, and resilience under unpredictable demand.
Code & Design Reviews. Contribute production code in critical paths,: review designs and implementations, and make architectural decisions including build-vs-buy tradeoffs with long-term operational consequences.
Production Leadership . Lead on the hardest production issues and: cross-system bottlenecks. Drive observability, incident response, capacity planning, and post-incident improvement with a high standard for operational rigor.
Technical Strategy Beyond Your Team. Drive platform-wide decisions across: adjacent teams on reliability, API design, capacity planning, and deployment strategy through strong technical judgment. Translate product and business requirements into scalable system designs and drive alignment on shared infrastructure decisions.
What they're looking for
- Mentorship. Raise the quality of technical decision-making across teams: through design feedback, pairing, and clear engineering standards.
- + years of experience in software engineering, with substantial individual: contributor 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, demonstrated through systems you built directly.
