About the Company
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.
About The Role
We’re hiring a full-stack engineer to build the critical parts of the Cerebras Developer Console — the primary interface developers and enterprises use to run and manage inference workloads.
This is a deeply technical, end-to-end role. You’ll build high-quality frontend systems (Next.js, TypeScript) and design backend services (GraphQL, Postgres, Redis) that power usage tracking, billing, quotas, and observability. The systems you build will operate at high scale, require careful data modeling, and balance real-time and batch processing. You’ll be expected to make strong architectural decisions and move quickly from idea to production.
Responsibilities
- Build and evolve core systems — design and implement APIs, services, and UI that power the Developer Console and scale with growing customer usage.
- Make architectural decisions — define system boundaries, data models, and tradeoffs across real-time vs batch processing, performance, and cost.
- Drive projects from 0 → 1 → scale — take ambiguous problems, define solutions, and deliver them to production.
- Partner with product and design — shape developer-facing workflows and experiences.
Requirements
- Technical depth in backend systems — strong fundamentals in APIs, data modeling, and distributed systems; experience with high-scale or real-time systems is a plus.
- Full-stack capability — comfortable working across frontend and backend, with the ability to make pragmatic tradeoffs.
- Strong technical judgment — you make sound architectural decisions and know when to optimize vs move fast.
- Ability to operate without structure — you bring clarity to ambiguous problems and drive execution independently.
- High standards for quality — you care about correctness, maintainability, and long-term system health.
- Bias for action — you move quickly, unblock yourself and others, and focus on impact.
- Experience in fast-moving environments — comfortable with shifting priorities and evolving scope.
- Experience — typically 1-3 years of industry experience building and operating production systems.
- Education — Bachelor’s or master's in computer science (or equivalent practical experience).
Conditions
- 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.