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Absolute Security Jobs in Ontario (NOW HIRING)

CARFAX

Senior Software Engineer - Dev Ops

London, ON

... at the absolute cutting edge of the AI industry -- this role was built for you. At CARFAX, we ... Security & Compliance -- Engage actively in the vulnerability assessment and remediation program ...

CARFAX

Senior Software Engineer - Dev Ops

London, ON · On-site

... at the absolute cutting edge of the AI industry -- this role was built for you. At CARFAX, we ... Security & Compliance -- Engage actively in the vulnerability assessment and remediation program ...

CARFAX

Senior Software Engineer - Dev Ops

London, ON

... at the absolute cutting edge of the AI industry - this role was built for you. At CARFAX, we ... Security & Compliance - Engage actively in the vulnerability assessment and remediation program ...

Chanel

Sales & Stock Support

Toronto, ON · On-site

CA$55K/yr

Ensure absolute confidentiality of the Company's commercial activities and internal affairs at all ... Financial Security - A strong company pension plan and bonus program to help you plan for the ...

1Valet

Sales Associate (Ontario)

Toronto, ON

$60K/yr

The absolute core of this position rests on two primary pillars: acquiring and enabling Channel ... Actives source, pitch, and bring new Channel Partners-including security integrators and low ...

CHANEL

Sales & Stock Support

Toronto, ON · On-site

CA$55K/yr

Ensure absolute confidentiality of the Company's commercial activities and internal affairs at all ... Financial Security - A strong company pension plan and bonus program to help you plan for the ...

CHANEL

Assistant Boutique Manager

Toronto, ON

Ensure absolute confidentiality of the Company's commercial activities and internal affairs at all ... Financial Security - A strong company pension plan and bonus program to help you plan for the ...

Chanel

Assistant Boutique Manager

Toronto, ON · On-site

Ensure absolute confidentiality of the Company's commercial activities and internal affairs at all ... Financial Security - A strong company pension plan and bonus program to help you plan for the ...

GEOX

Full Time Key Holder - Mapleview Mall

Burlington, ON · On-site

CA$17.80/hr

At GEOX our vision is to put our absolute best in everything we do. We are always open to changing ... Loss Prevention & Security: follow all operating and cash management policies & procedures to ...

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All JobsAbsolute Security JobsAbsolute Security Jobs in Ontario

Absolute Security information

See Ontario salary details

$9

$26

$75

How much do absolute security jobs pay per hour?

As of Aug 6, 2026, the average hourly pay for absolute security in Ontario is $26.29, according to ZipRecruiter salary data. Most workers in this role earn between $13.22 and $30.77 per hour, depending on experience, location, and employer.

What are the key skills and qualifications needed to thrive in the absolute security position, and why are they important?

To excel in an Absolute Security position, candidates generally require a solid understanding of security protocols, risk assessment, and emergency response, supported by relevant training or certification such as a security guard license. Familiarity with surveillance systems, access control tools, and incident reporting software is often essential in this role. Excellent observation skills, attention to detail, and strong communication help individuals stand out when monitoring premises and interacting with clients or the public. These qualities are vital for ensuring a safe environment, preventing security breaches, and effectively managing incidents as they arise.

What is an absolute security?

An Absolute Security job typically involves protecting people, property, and assets from threats such as theft, vandalism, or unauthorized access. Responsibilities may include monitoring security systems, patrolling designated areas, and responding to incidents. Depending on the role, you may work in corporate security, event security, or cybersecurity. Strong observational skills, attention to detail, and the ability to handle emergencies are essential. Some positions may require certifications or specialized training.

What are the typical daily responsibilities for someone working in absolute security?

In an Absolute Security role, you can expect to perform regular patrols of assigned areas, monitor security cameras, check credentials, and respond quickly to any suspicious activity or emergencies. Documenting incidents, collaborating with law enforcement if necessary, and maintaining reports are also common tasks. Many positions involve both indoor and outdoor work environments, and hours may vary depending on the location's needs. Teamwork is often essential, as you'll communicate frequently with other security professionals and site management to uphold strict safety standards.

What are popular job titles related to Absolute Security jobs in Ontario? For Absolute Security jobs in Ontario, the most frequently searched job titles are:
What job categories do people searching Absolute Security jobs in Ontario look for? The top searched job categories for Absolute Security jobs in Ontario are:
What cities in Ontario are hiring for Absolute Security jobs? Cities in Ontario with the most Absolute Security job openings:
Absolute Security jobs near you
Infographic showing various Absolute Security job openings in Ontario as of August 2026, with employment types broken down into 84% Full Time, 13% Part Time, and 3% Contract. Highlights an 92% Physical, 3% Hybrid, and 5% Remote job distribution, with an average salary of $54,679 per year, or $26.3 per hour.

Senior Software Engineer - Dev Ops

CARFAX

London, ON

Full-time

Medical, Retirement

Re-posted 10 days ago

Job description

Join Team CARFAX as a Senior Software Engineer - Dev Ops
 
We are looking for a seasoned Senior Software Engineer - Dev Ops to join our platform team and take an active role in designing, scaling, and operating the infrastructure that powers Large Language Model (LLM) development and hosting. This is a high-impact, highly technical position where you will own critical platform components, drive architectural decisions, and directly shape the reliability, performance, and security of our AI infrastructure.
 
At its core, this is a Kubernetes-first, cloud-native platform engineering role. We care deeply about your ability to architect and operate scalable, resilient infrastructure for LLM workloads — the specific cloud or tooling you've built that experience on is secondary. Our current platform runs on AWS with EKS, Flyte, ArgoCD, JupyterHub, and the LGTM observability stack, and you'll be working within that environment — but we are far more interested in the depth of your platform thinking than in a specific vendor background.
 
If you are an engineer who thrives at the intersection of AI/ML and cloud-native infrastructure, who gets excited about solving the unique scaling and operational challenges that LLM workloads demand, and who wants to work on technology that sits at the absolute cutting edge of the AI industry — this role was built for you.
 
At CARFAX, we believe in the power of teamwork and value in-person interactions so that we can collaborate and thrive together. This position will require 2 days in the London, ON office per week, subject to change with future business needs. One last thing: Our four-day week continues in Summer 2026! 
 
What You'll Own:
 
LLM Platform Architecture — Actively participate in the design and evolution of the core infrastructure platform supporting LLM training, fine-tuning, and inference workloads at scale, contributing architectural decisions that balance performance, cost, and reliability across the full platform lifecycle.
 
Kubernetes & Advanced Autoscaling — Own the design and implementation of sophisticated K8s autoscaling strategies (HPA, VPA, KEDA, Cluster Autoscaler) tailored to the highly variable and GPU-intensive demands of LLM workloads. Our current environment is EKS, though equivalent production Kubernetes experience on GKE, AKS, or on-prem is equally valued.
 
ML Workflow Orchestration — Participate in the engineering and optimization of ML pipeline infrastructure, contributing to best practices for pipeline design, resource allocation, and workflow reliability across LLM training and evaluation workloads. We currently use Flyte — experience with comparable platforms such as Kubeflow, Airflow, or Prefect translates well.
 
AI Developer Platform — Own and contribute to the architecture and operations of interactive compute environments used by AI researchers and LLM engineers to develop, experiment, and prototype. We run JupyterHub today, though experience with equivalent multi-user ML development platforms is directly applicable.
 
CI/CD & GitOps — Participate in the development and ongoing improvement of GitOps workflows and CI/CD pipelines, contributing to deployment best practices and enabling rapid, reliable delivery of platform changes. Our current implementation uses ArgoCD — strong experience with GitOps principles and comparable tooling is what matters.
 
Observability & Reliability — Contribute to the full observability stack implementation — designing dashboards, defining SLOs, building alerting frameworks, and ensuring deep visibility into LLM workload performance and platform health. We use the LGTM stack (Loki, Grafana, Tempo, Mimir) — experience with Prometheus, OpenTelemetry, ELK, Datadog, or equivalent platforms is welcomed.
 
Cloud Infrastructure — Participate in cloud infrastructure design across compute (including GPU instance families), storage, networking, and IAM, with a strong emphasis on cost optimization and operational excellence. Our primary cloud is AWS — candidates with strong GCP or Azure backgrounds who are prepared to work in AWS are encouraged to apply.
 
Security & Compliance — Engage actively in the vulnerability assessment and remediation program across all platform components, contributing to security standards and ensuring the LLM platform meets organizational and regulatory compliance requirements.
 
Collaborative Engineering — Participate in technical design reviews, contribute to roadmap discussions, and serve as a knowledgeable resource and collaborative partner across AIOps and MLOps disciplines
 
Required Experience & Skills:
 
7+ years of experience in DevOps, Platform Engineering, MLOps, or a closely related infrastructure discipline.
 
Deep Kubernetes expertise — production experience operating Kubernetes at scale on any major managed platform (EKS, GKE, AKS) or on-premises, with advanced knowledge of scheduling, autoscaling, networking, RBAC, and cluster operations.
 
Cloud infrastructure proficiency — extensive experience designing and operating production workloads on at least one major cloud provider (AWS, GCP, or Azure), covering compute, storage, networking, and identity and access management
 
MLOps / AI Infrastructure experience — demonstrated experience building and operating infrastructure that supports ML training, model serving, or LLM workloads, including GPU resource management and scheduling at scale
 
CI/CD & GitOps — strong hands-on experience with GitOps principles and modern CI/CD pipeline design, using any mainstream tooling (ArgoCD, Flux, GitHub Actions, Tekton, or equivalent)
 
Observability Engineering — production experience designing and operating observability platforms including metrics, logging, and distributed tracing, using any modern stack (Grafana/LGTM, Prometheus, Datadog, ELK, or equivalent)
 
Infrastructure as Code — strong proficiency with Terraform, Helm, or comparable IaC and configuration management tooling.
 
Programming & Scripting — solid coding ability in Python and/or Go, with experience writing automation, tooling, and infrastructure integrations.
 
Security Mindset — hands-on experience with vulnerability scanning, remediation workflows, and cloud security best practices including RBAC hardening and secrets management
 
Strongly Preferred:
Direct experience with Flyte or comparable ML workflow orchestration platforms (Kubeflow, Airflow, Prefect, Metaflow)
Experience operating JupyterHub or equivalent multi-user interactive compute platforms at scale
Familiarity with LLM-specific infrastructure — model serving frameworks (vLLM, Triton, TorchServe), GPU cluster management, large-scale distributed training setups
Hands-on experience with AWS (EKS, EC2 GPU families, S3, IAM, VPC) as our current primary cloud environment
Experience with FinOps practices — cloud cost attribution, rightsizing, and spot/preemptible instance strategies for ML workloads
Relevant certifications: CKA / CKS, AWS/GCP/Azure Solutions Architect or DevOps Engineer, or equivalent
Who You Are:
A systems thinker who understands how architectural decisions ripple across reliability, performance, cost, and security — regardless of which cloud or tooling stack those decisions are made within
Operationally minded — you build things to be observable, maintainable, and resilient from day one
Deeply curious about AI and LLMs — you understand why the infrastructure you build matters and stay current with how the AI landscape is evolving
Proactive and ownership-driven — you identify problems before they become incidents and drive solutions to completion
An effective collaborator and communicator who can translate complex infrastructure concepts for AI researchers, data scientists, and engineering leadership alike
Comfortable operating with autonomy in a fast-moving environment where priorities evolve alongside the AI landscape
 
Why This Role Stands Out:
LLM infrastructure is one of the most technically demanding and strategically important engineering domains in the industry today. As a senior member of our AIOps team you will:
Directly shape the platform that enables LLM development and productionization — your contributions will have immediate, measurable impact
Work on genuinely hard infrastructure problems — GPU scheduling, large-scale distributed workloads, high-throughput model serving, and multi-tenant ML environments
Be positioned at the epicenter of the AI infrastructure space, one of the fastest growing and highest-demand engineering disciplines in the industry
Have a clear voice in technical direction — your experience and opinions on platform design are genuinely valued and actively sought
Bring your full experience to the table — whether you've built on AWS, GCP, Azure, or hybrid environments, your platform engineering expertise is what drives impact here
 
What’s in it for you: 
  • Competitive Compensation: Attractive salary, comprehensive benefits, and generous time-off policies. 
  • Flexible Work Schedules: Enjoy 4-day summer work weeks and a winter holiday break. 
  • Retirement Support: 401(k) / DCPP matching. 
  • Performance Rewards: Annual bonus program to recognize your contributions. 
  • Innovative Workspace: Casual, dog-friendly offices designed for creativity and collaboration. 
 
Hear from our Team: Our accolades speak for themselves:
  • 10X Virginia Business Best Places to Work
  • 9X Washingtonian Great Places to Work
  • 9X Washington Post Top Workplace
  • St. Louis Post-Dispatch Best Places to Work
Vacancy Status:
This posting is for an existing vacancy.
 
Base Salary:
The anticipated base salary range for this position is CAD $92,500 to $136,000 annually. Final base salary will be determined based on geographical location, experience, and qualifications.
 
Benefits:
Join a company that values your total wellbeing. Carfax offers competitive compensation, comprehensive healthcare coverage, and the chance to make a meaningful impact in an industry-leading organization.  Our benefit offerings can be found at: CARFAX Careers.