AI Architect – T & I

Radio-Canada

AI Architect designing technology infrastructure at CBC/Radio-Canada. Optimizing AI models and mentoring engineers for media production workflows.

Posted 7/23/2026contractMontreal • 🇨🇦 CanadaMid-LevelSeniorWebsite

Core Competencies

Role fit

Core Competencies

Use this summary to align your resume positioning with the role.

Demonstrates expertise in designing and optimizing AI/ML solutions, with a strong focus on large-scale system architecture and performance engineering. Proficient in integrating AI technologies within media production environments while mentoring engineering teams.

Highest-signal resume keywords

AI/ML Solution DevelopmentLarge-Scale ML System DesignCloud Platform Experience (AWS, Azure, GCP)AI Frameworks (TensorFlow, PyTorch, Hugging Face)Bilingual Communication (English and French)

ATS Keywords

Tailor your resume

Applicant Tracking System Keywords

Tip: use these terms in your resume and cover letter to boost ATS matches.

Hard Skills

Machine LearningDeep LearningModelOpsAI EngineeringDevOpsMLOpsTechnical DocumentationCost Efficiency OptimizationInference Systems DesignGPU Infrastructure Optimization

Soft Skills

MentoringCollaborationCommunication

Tools & Technologies

DockerKubernetesMedia Production Platforms (MAM/PAM)CI/CD PipelinesVirtualizationNetworkingStorage

Industry Keywords

AI Solutions IntegrationHigh-Performance Training SystemsLanguage ModelsOperational ConstraintsScalable Enterprise AI Solutions

Tech Stack

Tools & technologies

AWSAzureCloudDockerGoogle Cloud PlatformKubernetesPyTorchTensorflow

About the role

Key responsibilities & impact

Design and plan CBC/Radio-Canada’s future technology infrastructure
Optimize Models, Inference and GPU Infrastructure
Design and build high-performance training and inference systems for LLMs and multimodal AI models
Collaborate with the Technology & Infrastructure (T&I) team to design, right-size and evolve our internal GPU cluster
Plan and develop the integration of AI solutions within CBC/Radio-Canada’s media production environments
Mentor and elevate the organization’s engineers and data scientists in large-scale ML system design and performance engineering

Requirements

What you’ll need

Bachelor's or master's degree in software engineering, information technology, artificial intelligence, mathematics or a related natural science field
Functional bilingualism (English and French) essential for Canada-wide communications
At least five years’ proven experience developing and deploying AI/ML solutions
At least eight years’ experience building tools and platforms in a software engineering role
Demonstrated experience working with language models and designing solutions optimized for cost efficiency and scale
Strong conceptual understanding of LLM, RAG and AI agent architectures, including their frameworks and operational constraints
Experience selecting AI framework architectures (e.g., TensorFlow, PyTorch, Hugging Face), cloud platforms (Azure, AWS, GCP) and orchestration tools (Docker, Kubernetes) for scalable enterprise AI solutions
Knowledge of ModelOps, AI engineering, DevOps and MLOps practices (including CI/CD pipelines)
Solid understanding of machine learning and deep learning fundamentals
Strong technical documentation skills, with the ability to produce diagrams, demos and technical artifacts that make AI architectures understandable and actionable
Hands-on technical experience working with media production platforms (MAM/PAM) and designing scalable solutions in a highly available, 24/7 environment
Solid working knowledge of cloud technologies (AWS, Azure or GCP), virtualization, networking and storage.

Benefits

Comp & perks

Flexible work arrangements
Professional development