Principal Engineer, AI Inference Reliability

Cerebras Systems; Toronto; On-site; CAD 120,000 - 150,000; Full time

Job summary

A cutting-edge AI technology company in Toronto is seeking a Reliability Tech Lead to drive the reliability strategy across their AI inference stack. You will define SLOs, lead incident management, and collaborate with multiple engineering teams to ensure a world-class service. The ideal candidate has 7+ years of experience in reliability engineering and strong programming skills in languages like Python or C++. This role offers a dynamic work environment focused on innovation and growth.

Benefits

Job stability with startup vitality

Non-corporate work culture

Opportunities for personal growth and learning

Qualifications

• 7+ years of experience in backend, infrastructure, or reliability engineering.
• Deep experience with SLO/SLI/SLA design and incident response.
• Excellent communication and leadership skills.

Responsibilities

• Define and drive reliability strategy and establish SLOs.
• Design and implement reliability mechanisms across systems.
• Lead large-scale incident management and postmortem analysis.

Skills

Backend programming

Reliability principles

Incident response

Cross-functional leadership

Education

Bachelor's or master's degree in computer science

Tools

Python

C++

Go

Rust

Job description

About the team

Cerebras Inference team’s mission is to deliver the world’s most performant, secure, and reliable enterprise‑grade AI service. We build and operate large‑scale distributed systems that power AI inference at unprecedented speed and efficiency. Join us to help scale inference and accelerate AI.

About the role

We’re looking for a hands‑on Reliability Tech Lead (IC) to own the mission of making Cerebras Inference the most reliable AI service in the world. You will drive reliability strategy and execution across our inference stack, from client SDKs and public‑cloud multi‑region deployments to wafer‑scale systems in specialized data centers.

In this role, you will define SLOs and incident‑response frameworks, design and implement reliability mechanisms at scale, and partner across hundreds of engineers to ensure our service meets world‑class reliability standards.

Si you are passionate about building and operating massive‑scale, low‑latency, high‑reliability distributed systems, we want to hear from you.

Responsibilities

• Define and drive reliability strategy: establish SLOs and ensure alignment across engineering.
• Design and implement reliability mechanisms: build and evolve systems for fault detection, graceful degradation, failover, throttling, and recovery across multiple regions and data centers.
• Lead large‑scale incident management: own postmortems, root‑cause analysis, and prevention loops for reliability‑related incidents.
• Architect for reliability and observability: influence system design for redundancy, durability, and debuggability.
• Develop reliability tooling: create internal tools and frameworks for chaos testing, load simulation, and distributed fault injection.
• Collaborate broadly: work across software, infrastructure, and hardware teams to ensure reliability is embedded into every layer of our inference service.
• Monitor and communicate reliability metrics: build dashboards and alerts that measure service health and provide actionable insights.
• Mentor and influence: guide engineers and set best practices for designing, testing, and operating reliable large‑scale systems.

Skills & Qualifications

• Bachelor’s or master’s degree in computer science or related field.
• 7+ years of experience in backend, infrastructure, or reliability engineering for large‑scale distributed systems.
• Strong programming skills in at least one popular backend programming language such as Python, C++, Go, or Rust.
• Deep and hard‑earned experience of reliability principles: SLO/SLI/SLA design, incident response, and postmortem culture.
• Excellent communication and cross‑functional leadership skills.
• Bonus: prior experience building large‑scale AI infrastructure systems.

Why Join Cerebras

• Build a breakthrough AI platform beyond the constraints of the GPU.
• Publish and open source your 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.

Read our blog: Five Reasons to Join Cerebras in 2025.

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.

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