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Added 17 days ago
Principal AI Engineer
PointClickCare
Mississauga, ON
$191,700 to $213,000 CAD / year
Full-time
PointClickCare is searching for a Principal AI Engineer who will lead and design AI systems across multiple SaaS solutions following our AI Design Patterns, defining technical standards and…
Added 18 days ago
Principal AI Engineer
PointClickCare
Mississauga, ON
Full-time
PointClickCare is searching for a Principal AI Engineer who will lead and design AI systems across multiple SaaS solutions following our AI Design Patterns, defining technical standards and…
Added 1 month ago
Principal AI Engineer
PointClickCare
Mississauga, ON
$191,700 to $213,000 CAD / year
Full-time
The Principal AI Engineer will design and architect scalable, secure, and enterprise-grade AI/ML platforms and solutions that enable product teams to rapidly build and deploy AI…
Added 1 month ago
Principal AI Engineer
PointClickCare
Mississauga, ON
Full-time
The Principal AI Engineer will design and architect scalable, secure, and enterprise-grade AI/ML platforms and solutions that enable product teams to rapidly build and deploy AI…
Added 1 month ago
Principal AI Engineer
Questrade Financial Group
Toronto, ON
We’re looking for our next Principal AI Engineer. Could It Be You?
Added 6 days ago
Principal AI Engineer
Mastercard
Toronto, ON
Full-time
Mastercard is seeking a Principal AI Engineer to design and deliver enterprise-scale AI platform capabilities that help teams build, deploy, evaluate, and operate AI-powered applications…
Added 1 month ago
Senior Principal AI Engineer
Questrade Financial Group
Toronto, ON
We’re looking for our next Senior Principal AI Engineer. Could It Be You?
Added 27 days ago
Principal Engineer, AI
BMO
Toronto, ON · BMOPLACE
Full-time
…AI safe, governed, and scalable. We are seeking experienced Principal/Senior engineers to build and operate the core infrastructure that governs how AI runs at BMO - the AI Gateway, Policy…
Added 27 days ago
Principal Engineer, AI Platform
BMO
Toronto, ON · BMOPLACE
Full-time
…AI safe, governed, and scalable. We are seeking experienced Principal/Senior engineers to build and operate the core infrastructure that governs how AI runs at BMO: the AI Gateway, Policy…
Added 1 month ago
Lead Python AI Principal Engineer (Hands-On), SVP
Citi
Mississauga, ON
Full-time
We are seeking a highly skilled, hands-on Lead Python AI Principal Engineer to join Citi in spearheading the design and development of cutting-edge AI platforms and services. This role…
Added 1 month ago
Lead Python AI Principal Engineer (Hands-On), SVP
Citi
Remote, Canada
Full-time · Remote
We are seeking a highly skilled, hands-on Lead Python AI Principal Engineer to join Citi in spearheading the design and development of cutting-edge AI platforms and services. This role…
Added 19 days ago
Principal Engineer, AI Production Readiness
Workday
Toronto, ON · Greater Toronto Area, Canada
Full-time
We are seeking a Principal AI Engineer to own the technical path that carries internally built AI agents from prototype to enterprise-grade production on Workday’s Databricks and AWS…
Added 17 days ago
Principal Engineer, AI & ML Solutions
Royal Bank of Canada
Vancouver, BC
Full-time
We are looking for a Principal Engineer, AI & ML Solutions, to join our Global Functions Technology (GFT) team! In this role you'll lead the building of a new AI product from the ground up…
Added 18 days ago
Principal Engineer, AI & ML Solutions
RBC
Vancouver, BC
Full-time
We are looking for a Principal Engineer, AI & ML Solutions, to join our Global Functions Technology (GFT) team! In this role you'll lead the building of a new AI product from the ground up…
Added 20 days ago
Principal Engineer, AI Production Readiness
Workday
Toronto, ON · Canada, ON, Toronto
Full-time
We are seeking a Principal AI Engineer to own the technical path that carries internally built AI agents from prototype to enterprise-grade production on Workday’s Databricks and AWS…
Added 27 days ago
Principal AI Engineer
Workday
Vancouver, BC · Canada, BC, Vancouver
Full-time
As a Principal AI Engineer in Agent Factory, you’ll design and build the core ML systems behind Workday’s next generation of AI agents. Working within a small, senior, cross-functional pod,…
Added 2 months ago
Principal AI Engineer - Tangerine
Tangerine
Toronto, Ontario
Full-time
Act as lead engineering partner to translate business requirements into responsible architectural patterns and best practices for agentic AI development, balancing innovation with risk and…
Added 9 days ago
Principal AI Engineer - Tangerine
Scotiabank
Toronto, ON
Act as lead engineering partner to translate business requirements into responsible architectural patterns and best practices for agentic AI development, balancing innovation with risk and…
Added 1 month ago
Principal Engineer, Cloud & AI
GeoLOGIC Systems Limited
Calgary, AB
We're growing and looking for a Principal Engineer, Cloud & AI to join our team. Geologic is building a new cloud-first product, designed from the ground up on modern technology with AI at…
Added 2 months ago
Principal AI Security Engineer
Cerebras Systems
Canada
Full-time
Cerebras is seeking a Principal AI Security Engineer to lead hands-on security engineering for enterprise IT, infrastructure, AI platforms, and agentic systems.
Added 18 days ago
Staff / Principal Software Engineer | Java + AI
Apexon
Toronto, ON
Contract
🚀 Hiring: Staff / Principal Software Engineer | Java + AI
Added 1 month ago
Principal Engineer - Gen AI training and inferencing
AMD
Markham, ON
$192,000 to $288,000 USD / year
Full-time
The AI Models and Applications team at AMD is looking for a specialized Principal level engineer who is passionate about enabling innovative and efficient Generative AI training/inferencing…
Added 4 months ago
Principal Software Engineer - AI
Boomi
Vancouver, British Columbia
Full-time
As a Principal Software Engineer, you will be a technical leader driving the design and implementation of complex backend systems at scale. You will set technical direction, guide team…
Added 11 days ago
Associate Principal Engineer - Snowflake AI Architect
Nagarro
Brampton, ON
Full-time
We are a Digital Product Engineering company that is scaling in a big way! We build products, services, and experiences that inspire, excite, and delight. We work at scale - across all…
Added 1 month ago
AI SDLC Engineer (Senior / Principal)
RAVL
Toronto, ON
Full-time
We're looking for a Senior / Principal AI SDLC Engineer to help our financial services clients modernize how software is built, secured, and delivered in an AI-enabled world.

Cerebras Systems

Principal AI Security Engineer

Canada

Job type: Full-time
Experience: 10+ years of experience in security engineering, platform security, infrastructure security, product security, or related technical security roles.
Posting language: English
Posted: Jun 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

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!

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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More about this job

Responsibilities

Lead the design and implementation of security controls for AI platforms, training and inference workflows, and agentic systems. Develop reusable security patterns and automate policy validation to protect sensitive data and customer environments.

Requirements

Requires over 10 years of experience in security engineering with strong proficiency in Python and cloud infrastructure, specifically AWS. Candidates must have deep knowledge of identity systems, runtime environments, and familiarity with AI/LLM security risks.

Skills

Python
AWS
IAM
Kubernetes
AI Security
LLM Application Security
Infrastructure as Code
OAuth
SSO
CI/CD
GitOps
Network Security
Identity and Access Management
Runtime Security
Security Architecture
Policy as Code

Visa sponsorship

Not detected in the job text

Keywords

AI Security
LLM
Agentic Workflows
MCP
Prompt Injection
AWS
IAM
Kubernetes
Python
Infrastructure as Code
GitOps
CI/CD
OAuth
SSO
Workload Identity
Zero-Standing-Privilege
Policy-as-Code
Model Serving
Inference
Training
Telemetry
Audit Logs
Runtime Enforcement
Distributed Compute
Secrets Management
Cloud-Native
Security Architecture
Developer Platforms
Cerebras
AI Chip

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