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Ai Platform Engineer Jobs in Quebec (NOW HIRING)

Our AI team, led by industry luminaries and veterans, is building GameFrame AI --a platform that allows developers to create complex, professional games using natural language. We are the creators of ...

Platform Engineer

Montreal, QC

CA$100K - CA$160K/yr

Qualifications & Skills: * 4 to 7 years of experience as a DevOps/SRE/Platform engineer * Extensive ... We may use artificial intelligence (AI) tools to support parts of the hiring process, such as ...

Align solutions to Manulife's Global AI Platform architecture, tooling, deployment patterns, governance standards, and approved engineering practices. * Operationalize AI solutions with testing ...

Experience with SQL and distributed data platforms (Spark, Databricks, or Snowflake). GOOD TO HAVE * Azure AI-102, AWS ML Specialty, or Google Professional ML Engineer certification. * Exposure to ...

Experience with SQL and distributed data platforms (Spark, Databricks, or Snowflake). GOOD TO HAVE * Azure AI-102, AWS ML Specialty, or Google Professional ML Engineer certification. * Exposure to ...

Specialization in at least one major AI platform ecosystem - Google (Gemini, Vertex AI, Gemini ... Claude Certified Developer - Foundations (Anthropic), Google Cloud Professional Machine Learning ...

Working closely with the AI Platform ProductManagement team, they will be the key technical owner ... Lead the engineering effort to integrate AI models into the SIMPRO core platform with velocity ...

We are seeking a Senior Cloud Platform Engineer to join our Central Technology Build Engineering ... Innovate with emerging build technologies, cloud and AI What You'll Bring: * Fundamental ...

The AI Product Manager , Innovation will shape and scale AI-powered products that deliver ... Partner with Data Scientists, Agentic Engineers, UX, platform engineering, architecture, security ...

... (SRE) practices. Governing enterprise AI solutions, including AI infrastructure, security and intelligent agent deployment. Ensuring platform availability, performance, resiliency and security.

Our engineers are the technical visionaries driving our innovative solutions. Renowned globally for ... Platform and MLOps * Support deployment and monitoring of AI solutions using Azure AI Services ...

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Ai Platform Engineer information

See Quebec salary details

$41K

$134.9K

$195K

How much do ai platform engineer jobs pay per year?

As of Aug 29, 2026, the average yearly pay for ai platform engineer in Quebec is $134,857.00, according to ZipRecruiter salary data. Most workers in this role earn between $110,500.00 and $157,500.00 per year, depending on experience, location, and employer.

What is an AI Platform Engineer?

AI Platform Engineers are technology professionals who design, build, and maintain the infrastructure that supports the development, deployment, and scaling of artificial intelligence (AI) and machine learning (ML) models. They work closely with data scientists and software engineers to ensure that AI solutions can run efficiently and securely in production environments. Their responsibilities often include managing cloud or on-premises platforms, automating workflows, and implementing best practices for model versioning, monitoring, and resource optimization.

How does an AI Platform Engineer typically collaborate with data scientists and software engineers in a project environment?

AI Platform Engineers often serve as a bridge between data scientists and software engineers, ensuring that machine learning models are seamlessly integrated into scalable, production-ready systems. They work closely with data scientists to understand model requirements and deployment needs, and with software engineers to embed these models within applications and services. This collaboration involves frequent communication, joint troubleshooting, and participation in code reviews to maintain a robust and efficient AI infrastructure.

What are the key skills and qualifications needed to thrive as an AI Platform Engineer, and why are they important?

To thrive as an AI Platform Engineer, you need strong programming skills (especially in Python and Java), a background in computer science or related fields, and experience with machine learning frameworks. Familiarity with cloud platforms (like AWS, Azure, or GCP), containerization tools (Docker, Kubernetes), and CI/CD systems is typically required, along with certifications such as Google Cloud Professional Machine Learning Engineer. Excellent problem-solving, collaboration, and communication skills help you integrate AI solutions across teams and projects. These competencies ensure the efficient development, deployment, and maintenance of scalable AI systems in dynamic production environments.

What is the difference between Ai Platform Engineer vs Data Engineer?

AspectAi Platform EngineerData Engineer
CredentialsBachelor's in CS, AI, or related; experience with cloud platformsBachelor's in CS, Data Science, or related; experience with databases and ETL tools
Work EnvironmentDeveloping AI infrastructure, deploying ML models, working with cloud servicesBuilding data pipelines, managing data storage, ensuring data quality
Industry UsageTech companies, AI startups, cloud providersFinance, healthcare, e-commerce, any data-driven industry

While both roles involve working with data and cloud platforms, Ai Platform Engineers focus on building and maintaining AI infrastructure and deploying machine learning models. Data Engineers primarily develop data pipelines and manage data storage. The roles often collaborate but serve different core functions within AI and data ecosystems.

How to become an AI platform engineer?

To become an AI platform engineer, you should have a strong background in computer science, software engineering, or related fields, with expertise in machine learning frameworks, cloud computing, and programming languages like Python or Java. Gaining experience with AI tools, data management, and infrastructure deployment is essential, often supported by certifications in cloud platforms such as AWS or Azure. Building a portfolio of projects and staying updated on AI and DevOps practices can also enhance your qualifications.

What does an AI platform engineer do?

An AI platform engineer designs, develops, and maintains the infrastructure and tools needed to deploy and manage artificial intelligence models at scale. They work with cloud services, programming languages, and machine learning frameworks to ensure efficient model training, deployment, and monitoring in production environments.

What is the salary of AI platform engineer?

The salary of an AI platform engineer typically ranges from $100,000 to $150,000 annually, depending on experience, location, and company size. Senior roles or those with specialized skills in cloud platforms and machine learning may earn higher compensation.

What are popular job titles related to Ai Platform Engineer jobs in Quebec?

For Ai Platform Engineer jobs in Quebec, the most frequently searched job titles are:

What job categories do people searching Ai Platform Engineer jobs in Quebec look for?

The top searched job categories for Ai Platform Engineer jobs in Quebec are:

Infographic showing various Ai Platform Engineer job openings in Quebec as of August 2026, with employment types broken down into 58% Full Time, 39% Part Time, and 3% Contract. Highlights an 78% Physical, 3% Hybrid, and 19% Remote job distribution, with an average salary of $134,857 per year, or $64.8 per hour.

AI Platform Engineer

Montreal, QC โ€ข Hybrid

Full-time

Medical, Dental, Vision, PTO

Posted 18 days ago


Job description

Introduction

At Ironbelly, we are fundamentally changing how video games are made. Our AI team, led by industry luminaries and veterans, is building GameFrame AI—a platform that allows developers to create complex, professional games using natural language. We are the creators of a battle-tested gameplay framework that has been used to build and launch AAA games, and we're leveraging that expertise to architect the future of creative software.

This isn't just another AI wrapper. You'll be engineering a production-scale AI orchestration system that coordinates specialized agents to manipulate Unreal Engine in real-time, building technology that has never existed before.

A Note on the Role: This is an Applied AI Engineering Position

To ensure we're connecting with the right candidates, let's be clear about the focus of this role:

  • We ARE looking for: A seasoned backend/platform engineer with production experience building complex systems that use AI models and frameworks (like LangChain, LLM APIs, LLM workflows).

  • This is NOT: A Machine Learning research or AI model-building role. We are not developing novel neural network architectures or training models from scratch.


What You'll Build ????️

As a Senior Software Engineer on our AI Platform, you will architect the intelligent backend that enables conversational game development.

  • Advanced Multi-Agent Orchestration: Design and build the core of GameFrame AI, implementing sophisticated multi-agent (LangGraph Swarm) and single-agent (ReAct) systems that translate user requests into concrete game development actions.

  • Gameplay Framework Integration: Engineer the crucial link between our AI systems and Unreal Engine, developing a robust translation layer that allows AI agents to programmatically configure our proprietary, component-based gameplay framework.

  • Production AI Infrastructure: Architect and scale a distributed, multi-user backend on cloud infrastructure (AWS/GCP, Kubernetes). You'll build everything from multi-provider LLM orchestration and hybrid memory systems to real-time streaming responses over WebSockets.

  • System Reliability & Observability: Implement enterprise-grade observability, monitoring, and robust failover systems required to support thousands of concurrent users with sub-second response times.


Who We're Looking For ????

We are seeking a strong software engineer who is passionate about building at the intersection of AI and game development.

Must-Have Experience:

  • Expert-Level Backend Engineering: Deep, production-level experience in Python (3.11+), building microservices with frameworks like FastAPI, and designing with async/await patterns.

  • Production Systems: Proven experience with PostgreSQL, Redis, real-time WebSocket systems, and container orchestration using Docker and Kubernetes in a cloud environment (AWS/GCP).

  • Applied AI Systems: 1+ years of hands-on experience building applications that leverage AI systems. You have practical, high-level experience with frameworks like LangChain/LangGraph and tooling like Claude Code.

  • Game Development Context: A strong understanding of Unreal Engine concepts (Actors, Components, Blueprints) and workflows, gained through at least 2 years of professional or significant personal project experience.

Nice-to-Have Experience:

  • Experience building production React applications with TypeScript and Next.js.

  • Advanced prompt engineering techniques (e.g., Chain-of-Thought).

  • Experience designing and implementing evaluation frameworks for AI agent performance.

Your Impact & Growth ????

  • First 90 Days: Architect and deploy the core agent systems for game creation, implementing multi-provider LLM orchestration and production-grade memory systems.

  • 6-12 Months: Scale the platform to support 500+ concurrent users, launch advanced agent capabilities, and build out continuous learning systems for our AI.

  • 12+ Months: Lead technical strategy as we scale to thousands of users, contribute to new industry patterns for AI-driven creative software, and help establish our position as thought leaders in the space.


Our Culture & Benefits ????

We are a passionate team based in

Montreal with a hybrid model that gets us collaborating in the office 1-2 days a week. We offer a competitive salary and a significant equity package with high growth potential.

Comprehensive Benefits: Health, dental, and vision package , plus flexible PTO.

  • Growth & Learning: A professional development budget for conferences, a hardware stipend, and dedicated research time to stay at the cutting edge.

  • Unique Perks: Opportunities for conference speaking, dedicated time for open-source contributions, and direct access to cutting-edge AI research partnerships.