AI Engineer

• AI Implementation - Design, build, and maintain all of our AI systems across the company. Everything from internal marketing, sales, finance, and operations systems to local AI systems in our engineering workflows, and the Chamber itself.
• AI Adoption - Educate, Train, Support, and Uplift everyone in the company with their AI adoption. Running office hours, making tutorials, providing resources, sourcing solutions, and more.
• AI Infrastructure - Architect and operate a scalable set of infrastructure that allows non-technical, and technical teams to use AI in a secure and productive manner.
• AI Systems & Agents - In conjunction with departments, design, build and maintain all AI systems and agents. This includes administering and managing our off the shelf AI systems like Claude, Viktor, Cursor, etc. It also includes our custom built Agents, Skills, Plugins, Tools, and more.
• AI Security - You are responsible for creating, maintaining, and enforcing all data, privacy, and security policies across our AI systems and Agents. Organization, Department, and Role based permissions and settings across all our products.
• Other Projects - As this is a technical role, you will also be asked to help build other internal systems like automations, micro apps, and more.

AI Solutions Lead

• 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

AI Architect – T & I

• Design, develop, and maintain AI agents and pipelines that integrate language models (LLMs) into member-facing features as well as internal tools
• Monitor performance, cost, reliability, and result quality of agents and pipelines in production, and implement the necessary tools to ensure their observability
• Integrate language model (LLM) APIs and third-party AI services into our Ruby on Rails environment and existing systems
• Evaluate and select the most appropriate AI tools, models, and services, considering their capabilities, cost, and reliability
• Collaborate with cross-functional teams to identify opportunities where AI can enhance member experience or optimize internal processes
• Diagnose issues and continuously improve deployed solutions in a fast-evolving field where models, tools, and best practices change rapidly

AI Developer

• As a Senior Engineer within the Internal AI Accelerator Squad, you will be at the forefront of Xero’s transformation into an AI-native company.
• You will act as a forward-deployed engineer, embedding yourself within various internal business teams to co-design and operationalise agentic AI workflows that remove manual toil and fundamentally reshape how our people work end-to-end.
• You will lead the delivery of high-stakes AI agents from discovery to production, while acting as a technical partner and evangelist.
• By defining the patterns, guardrails, and tooling for intelligent automation, you will create the blueprint that enables the rest of Xero to harness the power of AI safely and effectively.
• You will join a dedicated, high-velocity squad focused on boosting the adoption of agentic AI and intelligent automation across the global business.

Senior Engineer – AI Workflows

• Define and execute the technical strategy and roadmap for cloud and platform security engineering
• Architect scalable, end-to-end security data platforms supporting telemetry, risk analytics, compliance, and vulnerability management
• Establish engineering standards, secure-by-design principles, and best practices for data and platform security
• Translate complex, ambiguous security and business challenges into actionable, scalable technical solutions
• Lead solution architecture design, including threat modeling and alignment with enterprise security and regulatory requirements
• Oversee development and operation of cloud-based platforms processing high-volume security data (logs, alerts, audit trails)
• Ensure platform reliability through strong data quality, observability, governance, and performance management (SLA/SLO/KPI-driven)
• Drive automation of security controls, monitoring, and incident response processes
• Lead and develop engineering teams while partnering with cross-functional stakeholders to deliver secure, high-impact outcomes

AI Enablement Engineering Tech Lead

• Implement new product features &amp; support/ extend existing ones
• Build frontend platform components leveraged across our internal, external products and ecommerce storefronts like Shopify, Salesforce etc
• Work with product and design teams toTranslate product and design work (Figma) into robust, accessible, high-performance UI components&nbsp;
• Own frontend architecture decisions and uphold code-quality standards alongside other senior engineers, and mentor teammates through code review
• Contribute to development and maintenance of backend services using primarily Golang, Node.js
• Understanding of google cloud platform (GCP), CI/CD and be able to deploy code and infrastructure components
• Work with datastores like PostgreSQL, Cloud Spanner, BigQuery, and Bigtable
• Understand and implement RESTful or GraphQL APIs

Senior Fullstack Developer – AI

• Lead discovery with senior stakeholders to identify high-impact agentic use cases
• Translate complex business problems into production-ready AI system designs
• Architect secure, auditable agentic workflows (reasoning, tool use, data access, evaluation)
• Drive solutions from prototype to AltaForge production deployment (our internal agentic platform)
• Ensure all solutions align with AltaForge architecture for reusability and scale
• Define and enforce evaluation standards to measure outcomes and value creation
• Support account growth by ensuring successful delivery and lifecycle value realization

Senior AI Architect

• Bring novel ideas and the content of scientific papers into high-performing and robust scientific code.
• Lead the ideation, benchmarking, and execution of complex datasets and ML models, ensuring seamless integration into large-scale simulation frameworks.
• Drive software through the entire product lifecycle—from foundational research and implementation to launch and long-term support—ensuring technical excellence at every stage.

ML Research Engineer, AI for Life Sciences

• Lead the design and implementation of complex ML/AI systems end-to-end, owning architecture decisions and driving solutions from research through production at scale
• Build and evolve scalable ML platforms, pipelines, and infrastructure that support reliable, repeatable model development and deployment across teams
• Set the standard for AI-forward engineering, using tools like Claude and Cursor with sophistication and helping the team adopt them effectively
• Partner with product, engineering, and leadership to shape AI strategy and align technical direction with business outcomes
• Translate complex AI tradeoffs, risks, and opportunities into clear narratives that drive decision-making across technical and non-technical stakeholders
• Lead design reviews and technical discussions, raising the bar for engineering rigor and constructive challenge across the team
• Define AI architecture and engineering standards, bringing depth on tradeoffs, long-term implications, and responsible AI practices
• Mentor and grow junior and mid-level engineers, multiplying impact through coaching, code reviews, and pairing on hard problems
• Take ownership of the most ambiguous and highest-stakes pieces of work, driving them through to production with care for reliability, cost, and safety.

Staff AI Engineer

• Explore and apply frontier AI-enabled development tools and techniques in your daily work, and help assess where they add real value.
• Contribute to transforming the FME Flow codebase to support AI-assisted development — improving structure, documentation, and test coverage so AI tooling and engineers are effective.
• Work closely with the Principal Software Developer for AI Enablement to learn best practices, and help share and embed them within the Flow development team.
• Deliver reliable, maintainable code changes with growing independence, and troubleshoot and resolve issues with persistence.
• Participate in sprint and project planning, helping to anticipate risks and dependencies for your work.
• Collaborate across QA, UX, and Product, support more junior developers and interns, and contribute ideas that improve quality, workflow, and how the team uses AI.

Software Developer II, AI Enablement

• Design, develop, and operate large-scale, high-performance infrastructure that powers Confluent Cloud.
• Build foundational software to improve reliability, scalability, and efficiency across cloud environments.
• Work on distributed systems challenges such as consensus algorithms, failover strategies, and resource allocation.
• Collaborate with teams across Confluent to optimize and enhance infrastructure for real-time data streaming use cases.
• Troubleshoot and improve system reliability, observability, and performance across multiple cloud providers (AWS, Azure, GCP).

Senior Software Engineer – Streaming AI

• Work on Marketing Website and assist in developing new user-facing features using HTML, CSS, JavaScript and modern front-end frameworks
• Leverage AI coding assistants (e.g., GitHub Copilot, Claude, ChatGPT) to accelerate development, workflows and improve code quality
• Integrate AI-powered features into web interfaces, such as chatbots, personalized content recommendations, or AI-driven search functionality
• Refactor and write clean, reusable, and maintainable code with HTML, CSS, and JavaScript
• Work closely with design and backend teams to implement intuitive UI/UX designs, including AI-enhanced user experiences
• Experiment with prompt engineering to optimize AI tool outputs for development tasks
• Optimize components for speed, accessibility, and cross-browser compatibility
• Participate in team code reviews and agile development workflows
• Document AI workflows and best practices for the team

AI Developer, Intern/Co-op

• Reporting to the Director, AI & Digital Planning, the Senior AI Engineer will be responsible for using the latest AI tools to design, prototype, build, evaluate, and scale AI solutions including Generative and Agentic AI
• Define and document architectural patterns, technical standards, and design decisions
• Collaborate with internal teams to develop AI solutions
• Embed directly within clinical and operational teams to identify automation and agentic opportunities
• Manage the end-to-end lifecycle of AI solutions from design and development to implementation and sustainability
• Lead AI integration and implementation efforts within the hospital, and with partners
• Develop API endpoints and implement Model Context Protocols (MCPs) for exchanging healthcare information
• Connect AI agents to core hospital systems via APIs
• Design and implement techniques to optimize AI performance
• Build reliability and safety infrastructure for AI systems in a healthcare environment
• Ensure AI solutions comply with privacy, security, and responsible AI requirements
• Monitor and troubleshoot production issues

Senior AI Engineer

• Partner with domain teams to identify high-ROI use cases.
• Prototype, build, and own production ready (scalable, observable, secure) AI solutions, leveraging leading LLMs and Agentic AI platforms.
• Drive adoption of solutions through demos and user training.
• Improve productivity throughout the entire SDLC process with AI solutions, from Requirements and Design phase to Coding and Testing to Deployment and Runtime Operations.
• Improve AI-driven testing, troubleshooting, incident triaging, root cause analysis, and automation of repetitive workflows with verifiable outcomes.
• Build agentic automation, orchestrate multi-step workflows that plan tasks, call tools/APIs, and execute autonomously with clear guardrails.
• Implement RAG pipelines, ingest documents, create embeddings, index vectors, retrieve and rerank results, and ground outputs with citations.
• Develop system prompts, templates, and structured outputs (e.g., JSON) with versioning and evaluation.
• Set up tracing, relevance/factuality evaluations, and dashboards for cost, latency, and quality metrics.
• Contribute to best practices, patterns, and internal enablement materials.

Senior AI Developer

• Design, build, and maintain high-quality software systems and services.
• Work on a variety of technologies, frameworks, and platforms, adapting quickly as project needs evolve.
• Solve complex technical and logical problems with efficient and well-structured solutions.
• Leverage AI-powered development tools to accelerate development, debugging, research, and documentation.
• Collaborate with engineers, architects, and product stakeholders to deliver reliable solutions.
• Participate in code reviews, testing, and performance improvements.
• Continuously learn and experiment with new programming languages, frameworks, and technologies.
• Contribute ideas that improve engineering productivity, automation, and innovation.

Software Developer – AI Focus

• Design and evolve reusable GenAI workflow primitives and services used across Institutional Securities workflows
• Develop AI-powered assistants embedded into core Institutional Securities applications, leveraging agentic and tool-driven workflows
• Define and guide GenAI architecture decisions, including model selection, orchestration patterns, and evaluation strategies
• Establish and evolve LLMOps practices, including evaluation harnesses, prompt/version management, monitoring, and regression testing
• Design and implement controls for entitlements, data security, and PII handling, including usage of open-source models in regulated environments
• Partner with business and platform teams to drive adoption of shared GenAI capabilities across systems and workflows

Applied AI Engineering Specialist – Hybride

• Agentic AI Development & Deployment
• AI-Driven PDD & Automation Package Generation
• Prompt Engineering & Knowledge Systems
• Process Optimization & Automation Strategy
• Governance, Risk & Responsible AI

• Full-stack features across React, Node/Python, Postgres/Supabase, and AWS (Lambda, ECS, SQS, S3, Dynamo, RDS), N8n, and OpenAI Agents SDK
• LLM orchestration pipelines and agentic workflows that distill complexity into intuitive context/action architectures — always keeping the human in the loop
• A unified memory layer that blends relational, non-relational, and vector databases seamlessly
• AI-accelerated development tooling — spec-to-code pipelines, self-documentation, test scaffolding, and automations that make the team faster
• Modular, scalable infrastructure designed for heavy AI workloads and built to last

AI-Native Full-Stack Engineer

• Work closely with Enterprise Architect to design and implement solutions
• Research and pilot the latest GenAI technologies
• Champion a culture of continuous improvement and innovation
• Design, deploy, and manage API infrastructure on AWS
• Create and maintain technical design artifacts
• Use and enhance DevOps practices and tools
• Own deployment processes and establish CI/CD best practices
• Handle model components versioning across environments
• Support infrastructure automation and infrastructure-as-code practices
• Stay current with industry advancements in cloud technologies
• Provide post-production support for deployed applications

• Embed & deploy agents by tackling problems alongside teams
• Own deployments end-to-end: discovery, build, integration, activation, and tuning
• Lead pilots and demos, drive adoption, and clear blockers
• Build agentic systems with reasoning, planning, tool use, and coordination
• Design safe tool-use infrastructure across APIs, databases, and services
• Ship SDKs, patterns, and reusable blueprints for internal teams
• Design and run rigorous evaluations to measure quality and catch regressions
• Own multi-model inference for agents, focusing on latency and throughput
• Set technical direction and standards for agentic systems; mentor engineers

AI Engineer jobs in Canada

See all jobs on JobTailor

AI Solutions Lead

AI Architect – T & I

AI Developer

Senior Engineer – AI Workflows

AI Enablement Engineering Tech Lead

Senior Fullstack Developer – AI

Senior AI Architect

ML Research Engineer, AI for Life Sciences

Staff AI Engineer

Software Developer II, AI Enablement

Senior Software Engineer – Streaming AI

AI Developer, Intern/Co-op

Senior AI Engineer

Senior AI Developer

Software Developer – AI Focus

Applied AI Engineering Specialist – Hybride

AI Engineer

AI-Native Full-Stack Engineer

Senior AI Engineer

Senior AI Engineer