AI Architect (T & I) (Telework/Hybrid)

Position Title

AI Architect (T & I) (Telework/Hybrid)

Status of Employment

Permanent

Position Language Requirement

English, French

Language Skills

English (Reading - C - Advanced), English (Speaking - C - Advanced), English (Writing - B - Intermediate), French (Reading - C - Advanced), French (Speaking - C - Advanced), French (Writing - B - Intermediate)

Work at CBC/Radio-Canada

At CBC/Radio-Canada, we create content that informs, entertains and connects Canadians on multiple platforms. Our successes and accomplishments are driven by embodying and upholding values, which include creativity, integrity, inclusiveness and relevance.

Do you think you have the ability and drive to keep up with this exciting, ever-changing industry? Whether it be in front of the camera, on air, online or behind the scenes, you would be joining a team that thrives on making connections and telling stories that are important to Canadians.

Unposting Date

2026-09-14 11:59 PM

Behind the scenes, but ahead of the curve: help us develop the next-generation public service media organization.

Technology & Infrastructure (T&I) is the backbone and the future-forward arm of CBC/Radio-Canada. Our purpose is to constantly innovate to evolve and maintain the Corporation’s technology and infrastructure. We are the people that make stuff work. We make connections between media content, systems, people and places. We are the space in between.

A place with purpose. CBC/Radio-Canada has always been a highly regarded pioneer of media technology — not just in Canada but around the world. Today, we are transforming ourselves into a modern and agile public service media organization. Technology is the driving force, and we are the team making it happen.

This is a hybrid position with a mix of in-office and remote work. Work arrangements will be discussed with hiring managers per departmental guidelines.

Your Role

If you want to push the boundaries of media technology and are excited by the challenge of bridging creativity with cutting-edge tech, this role is for you!

As a key member of the Architecture and Strategic Development (Media System Architecture) team, you will design and plan CBC/Radio-Canada’s future technology infrastructure. Our mission is to transform our disparate media workflows by integrating hybrid agents, video understanding systems and advanced artificial intelligence architectures operating 24/7.

We are looking for an AI Architect with deep technical expertise in optimizing training and inference for large language models (LLMs), multimodal models and AI systems in a media context. As a technical thought leader, you will design robust systems to make AI faster, more scalable and more reliable, ensuring their seamless integration into our critical production ecosystems (PAM, MAM, studios).

Your Responsibilities

Optimizing Models, Inference and GPU Infrastructure

Design and build high-performance training and inference systems for LLMs and multimodal AI models.
Optimize end-to-end training, including high throughput data pipelines (streaming, sharding, bucketing), distributed training (parallelism strategies) and mixed precision.
Optimize inference and serving engines to guarantee minimum latency using KV caching design/management, batching, quantization and long-context processing.
Collaborate with the Technology & Infrastructure (T&I) team to design, right-size and evolve our internal GPU cluster into a new-generation infrastructure capable of supporting these massive workloads.

Strategy, Architecture and Media Ecosystem

Plan, develop and architect the integration of AI solutions within CBC/Radio-Canada’s media production environments (PAM, MAM, television and radio studios).
Evaluate and standardize integration protocols such as Model Context Protocol (MCP) and agent-to-agent (A2A) architectures to interconnect our models with complex production platforms (Avid, Dalet, Adobe).
Ensure absolute data security while developing video understanding systems that can interact with both file-based workflows (codecs, wrappers) and IP live workflows (SMPTE‑2110).

Technical Leadership, Mentoring and MLOps

Provide expert guidance on system efficiency, spearheading initiatives to dramatically improve architectural scalability, latency and reliability.
Mentor and elevate the organization’s engineers and data scientists in large-scale ML system design and performance engineering.
Develop robust MLOps/LLMOps pipelines with a constant focus on observability, performance profiling and automated testing.
Summarize and explain technological innovations to make them understandable to decision-makers and production teams and influence our strategic investments.

Featured Technology Environment

Inference Modelling and Optimization: PyTorch, vLLM, DeepSpeed, Accelerate, KV caching architectures, quantization techniques.
Infrastructure, Cloud and Compute: internal GPU clusters, distributed architectures, AWS, Azure, GCP, containers, Kubernetes.
Orchestration and Agents: Open WebUI, integration protocols (MCP, A2A), LiteLLM, LangChain, LangGraph, Strands.
Media Production: SMPTE-2110 protocols, PAM/MAM (Avid Interplay, Dalet), Adobe suite, media processing (audio/video codecs).
MLOps and Observability: Langfuse, Weights & Biases (W&B), MLflow, performance profiling tools.

Minimum Qualifications

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