Top AI Jobs in Montreal

Design, implement, optimize, and maintain performance-critical systems in Unreal Engine across Engine, Rendering, AI, or UI. Translate requirements into scalable C++ code, debug complex runtime issues, profile and optimize performance, integrate with artists/designers, mentor junior engineers, and contribute to technical architecture and engine customizations for production-ready game systems.

Ingénieur Système pour produits radar secondaires IFF : définir caractéristiques fonctionnelles, réaliser modélisation et simulations, développer traitements algorithmiques, proposer évolutions, intégrer progressivement l'IA, contribuer à l'architecture système, analyser données radar, valider algorithmes, résoudre problèmes d'intégration et supporter présentations clients et démonstrations.

The engineer will develop water management plans for mining projects, conduct hydrological studies, design hydraulic structures, and collaborate in multidisciplinary teams.

Participate in daily Scrum, review Jira tickets, debug and resolve issues, use Git for parallel development, collaborate on design and documentation, assist testing and performance troubleshooting. Basic English required; AI knowledge is a plus.

Ownership of backend features for Agentic Tools: design and implement GraphQL/REST APIs, build secure scalable Ruby on Rails services, improve RSpec automated tests, collaborate across product and AI teams, participate in Tier 2 on-call, and shape architecture for AI agent interactions with GitLab.

Manage, evolve and operate CI/CD platforms and infrastructure (GitHub Actions, Artifactory, Kubernetes) while integrating AI tools (Copilot, agents) to automate pipelines, ensure DevSecOps practices, define AI governance and security, and support development squads in adoption and continuous improvement.

Lead developer enablement to drive adoption of AI-powered coding tools across the firm. Run demos, workshops, and office hours; create reusable examples and guidance; collect developer feedback; define responsible usage and success metrics; partner with platform, risk, tooling, and engineering leaders to remove blockers and promote proven patterns in a regulated enterprise environment.

Develop and maintain AI-augmented healthcare application modules across C/C++/C#/Delphi stacks, debug complex integrations, produce tests and documentation with AI assistance, maintain clinical data integrations (HL7 v2), contribute to AI-enhanced features, participate in code reviews, and ensure regulatory compliance for Quebec health sector.

Lead live sessions, office hours, and project reviews for senior engineers transitioning into system architecture. Provide detailed architecture critiques, mentor students one-on-one, run architecture review boards, record instructional videos, conduct mock interviews, and coordinate supporting instructors to ensure high technical standards and student readiness for architecture roles.

Author and refine a systems-engineering curriculum for experienced engineers: shape syllabus, define learning objectives, produce and fact-check AI-assisted lessons, design hands-on projects, write rubrics and reviewer guides, and iterate with an LX designer. Part-time (15-20 hrs/week) for ~4-6 months.

The Principal Engineer will architect and own the Shop Builder platform, defining APIs, developing tools for developers and AI agents, and ensuring the platform's technical standards and documentation are met.

Lead a team to deliver tools and API solutions for the Shop Builder platform. Coordinate cross-team dependencies and maintain engineering standards while actively contributing code and driving technical decisions.

Lead strategy, roadmap, and execution for corporate website and customer web apps. Integrate AI across workflows, drive LLM-aware content/SEO, optimize performance, mentor full‑stack developers, and partner with design, product, and marketing to evolve the design system and improve conversions.

Design, build, and operate CI/CD, Kubernetes-based platforms, deployment automation, and observability for engineering workflows. Improve reliability, performance, and scalability across cloud and on-prem environments, debug cross-boundary failures, perform root-cause analysis, and deliver durable platform software and self-service tooling.

Execute hardware bring-up, validation, and telemetry monitoring for Cerebras AI clusters in data centers. Perform power-on sequencing, first-line troubleshooting, log collection, incident support under senior guidance, and contribute feedback to tooling and documentation while learning system architecture and networking fundamentals.

Design, implement, and maintain Python frameworks and services that orchestrate distributed engineering workflows across machines and clusters. Build scheduling, execution, resource management, failure recovery, and test infrastructure. Define APIs and abstractions, reason about concurrency and distributed-systems behavior, debug complex multi-system issues, write automated tests and documentation, and partner with platform, CI, release, QA, and product teams to deliver scalable infrastructure.

Early-career SDET on Release Integration Testing for Cerebras AI Inference Core. Write automation and tests across the AI stack, triage cross-stack failures, maintain branch stability, collect qualification evidence, and collaborate with feature and infra teams to prepare features for production release.

Design and build secure, scalable systems as a Full-Stack Software Engineer, leveraging expertise in Next.js, TypeScript, PostgreSQL, and AI tools to enhance cybersecurity within global infrastructure.

As a Backend/AI Systems Engineer, you will develop backend systems for AI workflows and enhance core functionalities for Spellbook's legal software. You'll tackle complex problems, ensure system reliability, and collaborate with product teams, while maintaining a hands-on ownership approach.

As a Senior Full-Stack Software Engineer, you will design, build, and ship AI-powered systems to optimize workflows in the single family rental market, focusing on backend services and full-stack development in a fast-paced environment.

As a Senior Full Stack Agentic AI Developer, you will design and implement scalable solutions, collaborate globally, and leverage GenAI tools to enhance AI development capabilities.

Evaluate AI-generated coding interactions, assess quality of engineering judgments, provide feedback, and define standards for AI coding agents. Comfortable making subjective judgments about engineering quality.

Design and develop full-stack applications for GenAI, focusing on efficient code in Python and TypeScript while maintaining system scalability and reliability.

Design, implement, and own a reusable on-device ML inference platform for resource-constrained devices. Integrate inference into RTOS firmware, develop drivers and DMA paths, debug on real hardware, train and optimize models for microcontroller-class hardware, and ship features to production while raising team expertise and using AI-assisted tooling.

You will manage the deployment of AI vision systems in manufacturing environments, integrating with OT/IT, troubleshooting, and training customer teams.