--- title: 'Principal Engineer, AI Inference Reliability at Cerebras Systems' canonical: 'https://feeny.ai/job/principal-engineer-ai-inference-reliability-cerebras-systems-united-states-and-kgdrh3yehwqh' type: 'job' last_seen: '2026-09-15' --- # Principal Engineer, AI Inference Reliability at Cerebras Systems - **Company:** [Cerebras Systems](https://feeny.ai/companies/cerebras-systems) - **Location:** United States and, Canada - **Employment:** full-time - **Posted:** 2025-10-29 - **Last confirmed live:** 2026-09-15 - **Apply:** https://jobs.ashbyhq.com/cerebras/088ab192-e04a-4819-8152-0d0f8c015299/application **Skills:** Python, C++, Go, Rust, SLO/SLI/SLA design, Incident response, Postmortem culture, Distributed systems, Backend engineering, Infrastructure engineering, Reliability engineering, Large-scale AI infrastructure systems > Cerebras Systems seeks a Principal Engineer to lead reliability strategy and execution for its high-performance AI inference service. The role involves defining SLOs, designing fault-tolerant systems, and managing large-scale incidents across distributed infrastructure. ## 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](https://openai.com/index/cerebras-partnership/) with Cerebras, to deploy 750 megawatts of scale, transforming key workloads with ultra high-speed inference. ## 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. If 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 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](https://www.cerebras.ai/join-us)! 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](https://www.cerebras.net/privacy/) to review our CCPA disclosure notice. ## About Cerebras Systems ## Company Overview - **One-liner**: Cerebras builds wafer-scale AI chips (the largest semiconductors ever made) and supercomputers that deliver up to 15x faster inference than GPUs, offered both on-premises and via cloud APIs. - **Entity Type**: Public (NASDAQ: CBRS) — filed for IPO and now listed on the Nasdaq. - **Headquarters**: Sunnyvale, California, United States - **Founded**: 2015 - **Founders**: Andrew Feldman, Gary Lauterbach, Michael James, Sean Lie, Jean-Philippe Fricker ## Core Business - **Primary industries**: Semiconductor manufacturing, AI computing hardware and software, cloud AI services. - **Target customers**: B2B – enterprises, government research labs, cloud service providers, and AI developers. - **Mission**: “Building impossible technologies so you can too” – accelerating AI through wafer-scale computing. ## Products & Services - **Wafer-Scale Engine (WSE-3)**: The world’s largest AI chip (215 mm²), 58x larger than a typical GPU, built for ultra‑fast AI training and inference. Manufactured by TSMC. - **CS-3 Supercomputer**: A single system powered by the WSE-3, delivering record-breaking AI performance for on-premises deployment. - **Cerebras AI Inference Cloud & Training Cloud**: Pay-as-you‑go APIs that provide drop‑in OpenAI‑compatible access to Cerebras’ hardware for serving, fine‑tuning, and pre‑training models. - **Condor Galaxy Network**: A series of supercomputers (e.g., CG‑1 with 4 exaFLOPs) built in partnership with G42 for high‑performance AI. ## Market Standing - **Valuation/Market Cap**: Not disclosed (recently public; market cap data not available in provided sources). - **Key Metric**: Annual revenue of $78.7 M (latest); total funding of $2.7 B across 15 rounds. - **Notable Investors/Partners**: G42, OpenAI (signed in 2026), Amazon Web Services (signed in 2026), Meta (Llama API), Perplexity, Mistral, Hugging Face, OpenRouter. - **Growth Signals**: - 34.3% YoY headcount growth (701 employees). - Rapid data center expansion across North America and Europe. - Won the HPCwire Readers’ & Editors’ Choice 2025 for Best AI Product/Technology. - Named to Forbes America’s Best Startup Employers 2026 and Fast Company Most Innovative Companies 2026 (AI). ## Competitive Advantages - **Wafer‑scale architecture**: Eliminates interconnect bottlenecks, reducing latency and delivering up to 15x faster inference than GPU clusters. - **Largest AI chip ever built**: 58x larger than any GPU, enabling massive on‑chip memory (SRAM) and compute density. - **Full‑stack offering**: Hardware + cloud APIs + on‑prem systems, giving customers deployment flexibility. - **Strong customer relationships**: Key contracts with OpenAI, AWS, G42, and Mayo Clinic (2024 Gordon Bell Prize work). ## Strategic Focus - **Scale inference capacity**: Building out data centers to become the world’s #1 provider of high‑speed AI inference. - **Deepen cloud partnerships**: Expanding pay‑as‑you‑go cloud access and enterprise deployments. - **Advance wafer‑scale technology**: Continuous R&D on WSE‑3 successors and software stack (compiler, ML workflows). - **Broaden model support**: Already serving Llama, Gemma, Qwen, Mistral, and more; integrating with Hugging Face and OpenRouter. ## Why Work Here - **Culture**: “Extraordinary people, breakthrough innovation, global impact” – the company highlights collaborative, low‑overhead teams with little bureaucracy. - **Work environment**: Hybrid/office with locations in Sunnyvale, San Diego, Toronto, and Bangalore. Inclusive and flexible policy. - **Perks**: Premium medical/dental/vision, life insurance, generous vacation, 401(k) and Group RRSP retirement plans, daily catered meals, healthy snacks, family‑friendly events (including CEO’s famous BBQ). - **Engineering focus**: Tackling fundamental challenges in chip design, system software, compiler technology, and ML workflows. Positions range from hardware (Design Verification, Manufacturing) to software (SRE, Compiler, Cloud). - **Philanthrophy**: Supports local communities and hosts students from around the world for Q&A. ## Sources 1. [cerebras.ai/company](https://www.cerebras.ai/company) 2. [cerebras.ai](https://www.cerebras.ai/) 3. [cerebras.ai/join-us](https://www.cerebras.ai/join-us) 4. [linkedin.com/company/cerebras-systems](https://www.linkedin.com/company/cerebras-systems) ## Other roles at Cerebras Systems - [Detection and Response Platform Engineer](https://feeny.ai/job/detection-and-response-platform-engineer-cerebras-systems-sunnyvale-gx4sa9aschnm) — Sunnyvale, CA - [Physical Security Lead, Manufacturing Operations](https://feeny.ai/job/physical-security-lead-manufacturing-operations-cerebras-systems-sunnyvale-s741d6wava3v) — Sunnyvale, CA - [Staff AI Engineer – Business Systems](https://feeny.ai/job/staff-ai-engineer-business-systems-cerebras-systems-sunnyvale-vgybt0ehv5wt) — Sunnyvale, CA - [Senior ERP Systems Administrator](https://feeny.ai/job/senior-erp-systems-administrator-cerebras-systems-sunnyvale-z6p5ssmrtw01) — Sunnyvale, CA - [DevOps Engineer Intern - PEY](https://feeny.ai/job/devops-engineer-intern-pey-cerebras-systems-toronto-8h2bj7zw2bd2) — Toronto, Canada - [Senior Operations Accountant](https://feeny.ai/job/senior-operations-accountant-cerebras-systems-sunnyvale-1sfperr2mr6m) — Sunnyvale, CA - [Software Engineer - Host and Network IO](https://feeny.ai/job/software-engineer-host-and-network-io-cerebras-systems-sunnyvale-tqykyeenvej3) — Sunnyvale, CA - [Staff GPU Inference SDET](https://feeny.ai/job/staff-gpu-inference-sdet-cerebras-systems-sunnyvale-p8ke5xg4qba1) — Sunnyvale, CA - [Network Security Engineer](https://feeny.ai/job/network-security-engineer-cerebras-systems-sunnyvale-s1q0rza0gbsf) — Sunnyvale, CA - [Distributed Software Engineer](https://feeny.ai/job/distributed-software-engineer-cerebras-systems-toronto-2y0byqqxk57d) — Toronto, Canada