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Added 4 mins ago
Senior Director, Enterprise Systems & AI Enablement
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Full-time
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Cerebras

Senior FE Engineer - Inference Console

Toronto, ON, Canada

Job type: Full-time
Apply by: Oct 15, 2026
Experience: Experience - typically 8+ years of industry experience building and operating production systems.
Posting language: English
Posted: Sep 23, 2026

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Original job description

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.

This order of magnitude increase in speed is transforming the user experience of AI applications, unlocking real-time iteration and increasing intelligence via additional agentic computation.

Cerebras works with the leading model labs, global enterprises, and cutting-edge AI-native startups. OpenAI recently announced a multi-year partnership with Cerebras, to deploy 750 megawatts of scale, transforming key workloads with ultra high-speed inference.

About The Role

We’re hiring a Senior Frontend Engineer to own and scale 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.

You’ll join an existing, high-velocity team and take ownership of major platform areas such as billing, request logs, and metrics. This is not a “ticket execution” role - you’ll define problems, drive technical direction, and lead execution across the stack. The work directly impacts customer experience and revenue, and the expectations are correspondingly high.

As a Senior Engineer, you’ll set the bar for engineering quality and execution. You’ll mentor engineers, drive design reviews, and push the team toward simple, scalable solutions. We’re looking for someone who thrives in fast-moving environments, operates with urgency, and is comfortable navigating ambiguity while shipping high-quality systems.

What You’ll Do

Own a major area of the platform - take end-to-end responsibility for systems such as billing, usage tracking, quotas, request logs, or metrics.
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.
Lead technical execution - break down work, align engineers, and ensure high-quality delivery across the stack.
Improve system reliability and visibility - ensure systems are observable, debuggable, and production-ready.
Partner with product and design - shape developer-facing workflows and experiences.

What We’re Looking For

Track record of ownership - you’ve led and delivered complex systems end-to-end, not just contributed components.
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.
Influence and mentorship - you elevate the team through design reviews, guidance, and leading by example.
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 8+ years of industry experience building and operating production systems.
Education - Bachelor’s or master's in computer science (or equivalent practical experience).

Why Cerebras

Cerebras is redefining the speed and scale of AI inference. The systems we build power real-world production workloads, not demos.

Work on systems that matter - you’ll build core platform infrastructure that directly impacts how customers run and scale AI workloads in production.
Own meaningful surface area - this is not a narrow role. You’ll take ownership of critical systems (billing, usage, observability) that sit at the heart of the platform.
Operate at the intersection of product and infrastructure - the work spans developer experience, distributed systems, and real-time data, requiring both strong engineering and product thinking.
High impact, low bureaucracy - you’ll work in a small, high-performing team where decisions are made quickly and engineers have real influence on direction.
Grow with the platform - as we expand from cloud offerings into broader infrastructure and cluster management, the scope and technical challenges will continue to grow.

Why Join Cerebras

About

People who are serious about software make their own hardware. At Cerebras, we have built a breakthrough architecture that is unlocking new opportunities for the AI industry. With dozens of model releases and rapid growth, we’ve reached an inflection point in our business. Members of our team tell us there are five main reasons they joined Cerebras:

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.

Find out more about what it's like to work at Cerebras here!

Apply today and become part of the forefront of groundbreaking advancements in AI!

Cerebras Systems is committed to creating an equal and diverse environment and is proud to be an equal opportunity employer. We celebrate different backgrounds, perspectives, and skills. We believe inclusive teams build better products and companies. We try every day to build a work environment that empowers people to do their best work through continuous learning, growth and support of those around them.

This website or its third-party tools process personal data. For more details, click here to review our CCPA disclosure notice.

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More about this job

Responsibilities

Own and scale major Developer Console platform areas, such as billing, usage tracking, quotas, request logs, and metrics, by building frontend interfaces, APIs, and backend services. Make architectural decisions, lead delivery across the stack, and improve system reliability, observability, and developer-facing workflows.

Requirements

Typically requires 8+ years of experience building and operating production systems, with strong backend fundamentals in APIs, data modeling, and distributed systems, plus the ability to work across frontend and backend. A bachelor's or master's degree in computer science or equivalent practical experience is expected, along with technical leadership, sound judgment, ownership, and comfort working in ambiguous, fast-moving environments.

Skills

Frontend Engineering
Full-Stack Development
Next.js
TypeScript
GraphQL
PostgreSQL
Redis
API Design
Data Modeling
Distributed Systems
Real-Time Systems
System Architecture
Observability
Technical Leadership
Mentorship

Visa sponsorship

Not detected in the job text

Keywords

Cerebras Systems
AI Inference
Developer Console
Frontend Engineering
Next.js
TypeScript
GraphQL
PostgreSQL
Redis
APIs
Backend Services
Billing
Usage Tracking
Quotas
Request Logs
Metrics
Observability
Data Modeling
Distributed Systems
Real-Time Processing
Batch Processing
System Architecture
Production Systems
Platform Infrastructure
Developer Experience
Technical Leadership
Design Reviews
Reliability
Inference Workloads
Semiconductor Manufacturing

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