---
title: 'Principal AI Security Engineer at Cerebras Systems'
canonical: 'https://feeny.ai/job/principal-ai-security-engineer-cerebras-systems-united-states-and-ym5q23kxackm'
type: 'job'
last_seen: '2026-09-15'
---

# Principal AI Security Engineer at Cerebras Systems

- **Company:** [Cerebras Systems](https://feeny.ai/companies/cerebras-systems)
- **Location:** United States and, Canada
- **Employment:** full-time
- **Posted:** 2026-06-23
- **Last confirmed live:** 2026-09-15
- **Apply:** https://jobs.ashbyhq.com/cerebras/dbeeb53b-1bfd-4454-8285-4ec5dbceebc3/application

**Skills:** Python, AWS, IAM, Networking, Secrets Management, Logging, Cloud-native Control Planes, SSO, MFA, OAuth, Service Accounts, Workload Identity, Authorization, Privileged Access, Least Privilege, Containers, Kubernetes, Isolated Workloads, Secure Development Environments, Distributed Compute Platforms

> Lead hands-on security engineering for enterprise IT, infrastructure, and AI platforms. Design and build security controls, reusable patterns, and production-ready systems to protect sensitive data, models, and agentic workflows.

## 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

Cerebras is seeking a Principal AI Security Engineer to lead hands-on security engineering for enterprise IT, infrastructure, AI platforms, and agentic systems. In this role, you will design and build security controls for systems that support training, inference, model serving, customer workloads, internal automation, and AI-assisted development. You will work across product, cloud, infrastructure, identity, runtime, data, and developer platforms to protect sensitive data, enterprise and customer environments, models, tools, agents, and control planes. This is a principal IC role for someone who can turn ambiguous AI and platform security risks into practical architecture, reusable controls, and production-ready systems that teams can adopt by default.

## Responsibilities

- Define security architecture and build controls for AI platforms, training and inference workflows, model-serving systems, customer workloads, developer workflows, and agentic
- Develop reusable AI and agent security patterns for identity, authorization, delegated authority, scoped tool access, MCPs, connectors, secrets, approvals, isolation, auditability, and
- Design runtime controls that constrain execution, access, data exposure, model and tool interaction, and blast radius.
- Build security capabilities as code using infrastructure as code, configuration as code, policy as code, GitOps, CI/CD, and automated validation.
- Define secure development patterns for AI systems, agents, prompts, tools, models, policies, evaluations, releases, and rollback.
- Automate security reviews, policy checks, evidence collection, control validation, and remediation
- Instrument AI, agent, and platform activity with telemetry, traceability, policy decisions, audit logs, anomaly signals, and response workflows.
- Lead hands-on security reviews and influence product, platform, infrastructure, and security architecture through practical design changes and reusable controls.

## Skills and Qualifications

- 10+ years of experience in security engineering, platform security, infrastructure security, product security, or related technical security roles.
- Strong hands-on engineering ability in Python and at least one additional production
- Experience designing, building, operating, and improving security controls as
- Strong cloud and infrastructure security experience, preferably with AWS, including IAM, networking, secrets management, logging, and cloud-native control planes.
- Deep understanding of identity and access systems, including SSO, MFA, OAuth, service accounts, workload identity, authorization, privileged access, and least privilege.
- Practical experience securing runtime environments such as containers, Kubernetes, isolated workloads, secure development environments, distributed compute platforms, or production service infrastructure.
- Familiarity with AI security, LLM application security, agentic workflows, MCPs, prompt injection, autonomous coding agents, or AI platform security.
- Ability to reason about cross-system risk involving identity, data, models, tools, networks, workflows, approvals, and automation.
- Strong written communication skills and the ability to influence senior technical stakeholders across Security, Product, IT, Infrastructure, and Engineering.

Relevant Experience We do not expect every candidate to have worked across all of these areas, but we value depth in several:

- AI, ML, training, inference, model-serving, or large-scale compute
- Coding agents, agent platforms, MCP servers, internal developer platforms, or AI-assisted development environments.
- Workload identity, secrets brokers, token brokers, short-lived credentials, privileged access, or zero-standing-privilege architectures.
- Policy-as-code, authorization services, runtime enforcement layers, or security control
- Software delivery security, including source control, CI/CD, build systems, artifacts, provenance, signing, and release gates.
- Detection, investigation, and response workflows for cloud, infrastructure, identity, AI, or agent

What Success Looks Like Success in this role means shaping how Cerebras secures the systems behind AI training, inference, model serving, customer workloads, and agentic automation. You will turn emerging AI and agent risks into reusable security architecture, safer identity and authorization models, scoped tool access, runtime containment, secure software delivery paths, automated policy validation, high-signal telemetry, and controls that engineering teams can adopt by default.

## 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