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Ai Integration Jobs in Quebec (NOW HIRING)

Superviser la livraison de projets BI, intégration de données et IA * Assurer la qualité des solutions : * Visualisation et rapports BI * Pipelines de données * Cas d'usage IA et analytique ...

$20.09 - $26.78/hr

Automation, AI/ML for Open RAN integrations Co-Op Position**Location: Ottawa, ON Canada Duration: Co-op/Intern 16 Months Start Date: Sep 8, 2026 Accepting applications until February 27, 2026 or ...

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About Axya Axya is building AI-powered technology to transform how manufacturers source and procure ... We are looking for an Integration Specialist to help connect our platform with customer systems ...

$140 - $210/hr

Own the architectural vision for how AI integrates into your domain -- from on‑device inference and cloud‑assisted pipelines to fully agentic decision workflows * Design AI‑native systems from ...

New

Rapid Prototyping & Integration: Lead the engineering effort to integrate AI models into the SIMPRO core platform with velocity, building on top of APIs and microservices that ensure high performance ...

A growing curiosity about industry, consumer and technology trends (including opportunities of AI integration) * Automotive experience - not obligatory

Select, configure, and integrate Claude , Microsoft Copilot , and other LLM solutions into durable ... Own and evolve the AI delivery platform stack leveraging Azure AI Foundry and other Microsoft Azure ...

AI Solutions Architect

Quebec, QC · On-site

$100 - $120/hr

Our technology ecosystem is built on Microsoft Fabric and Azure, integrating external large ... As our AI Solutions Architect , you'll play a key role in ensuring the integrity, scalability, and ...

$90 - $130/hr

About Mistral Mistral provides full-stack AI solutions: from frontier models to developer tools ... best production integration with back-end and front-end interfaces. * You'll work on ...

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Ai Integration information

What is a $900000 AI job?

A $900,000 AI job typically refers to a high-level position in artificial intelligence, such as AI research director, senior machine learning engineer, or AI solutions architect, often requiring advanced skills in programming, data analysis, and deep learning. These roles usually involve leadership, strategic planning, and expertise in tools like TensorFlow or PyTorch, with compensation reflecting experience and impact on business or technology development.

What are some common challenges faced when integrating AI solutions into existing business processes?

One of the most common challenges in AI integration is ensuring that new AI tools seamlessly interact with legacy systems and data formats. Team members often need to address data quality issues, adapt workflows, and manage stakeholder expectations regarding the capabilities and limitations of AI. Collaboration with IT, operations, and business units is essential to customize solutions and ensure user adoption. Additionally, ongoing monitoring and retraining of AI models is necessary to maintain performance and align with evolving business goals.

What is an AI integration job?

An AI integration job involves implementing artificial intelligence systems into existing software or workflows to improve functionality or automate processes. It requires skills in programming, data analysis, and understanding AI tools and platforms. Professionals in this role often collaborate with development teams and may need knowledge of machine learning, APIs, and cloud services.

How much does an AI integration specialist make?

An AI integration specialist typically earns between $70,000 and $130,000 annually, depending on experience, location, and industry. Professionals with skills in machine learning, programming, and cloud platforms tend to have higher salaries, especially in tech-focused environments.

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

To excel as an AI Integration Specialist, you need a solid background in computer science, proficiency in programming languages (such as Python), and experience with machine learning frameworks, often supported by a relevant degree or certifications. Familiarity with cloud platforms (like AWS, Azure, or Google Cloud), APIs, and integration tools is typically required. Strong problem-solving skills, effective communication, and the ability to collaborate across teams make someone stand out in this role. These competencies are crucial for successfully implementing AI solutions that align with business needs and ensuring seamless system interoperability.

What is AI integration?

AI integration refers to the process of incorporating artificial intelligence technologies into existing systems, applications, or business processes to enhance automation, improve decision-making, and optimize performance. This can involve connecting AI models, such as machine learning algorithms or natural language processing tools, with software platforms, databases, or workflows. The goal is to enable systems to analyze data, learn from patterns, and perform tasks that traditionally required human intelligence. AI integration can benefit a wide range of industries, including healthcare, finance, manufacturing, and customer service.

What is the difference between Ai Integration vs Data Analyst?

AspectAi IntegrationData Analyst
Required CredentialsBachelor's in Computer Science, Engineering, or related fields; knowledge of AI/ML toolsBachelor's in Statistics, Mathematics, or related fields; proficiency in data analysis tools
Work EnvironmentTech companies, AI development teams, software firmsBusiness, finance, healthcare, and other industries analyzing data
Employer & Industry UsageDeveloping AI solutions, integrating AI into productsInterpreting data, generating reports, supporting decision-making

While Ai Integration specialists focus on implementing AI systems and integrating AI technologies into applications, Data Analysts interpret data to provide insights and support business decisions. Both roles require analytical skills, but Ai Integration emphasizes technical development and system integration, whereas Data Analysts focus on data interpretation and reporting.

How to become an AI integration specialist with no experience?

To become an AI integration specialist with no experience, start by learning foundational skills in programming languages like Python and understanding AI concepts such as machine learning and APIs. Gaining hands-on experience through online courses, tutorials, and small projects helps build practical skills, while certifications in AI or cloud platforms can enhance your credentials. Entry-level roles may require demonstrating problem-solving abilities and familiarity with AI tools and frameworks.
What are popular job titles related to Ai Integration jobs in Quebec? For Ai Integration jobs in Quebec, the most frequently searched job titles are:
What job categories do people searching Ai Integration jobs in Quebec look for? The top searched job categories for Ai Integration jobs in Quebec are:

Gestionnaire, Donnees, AI & Integration

Pharmascience

Full-time

Re-posted 7 days ago


Job description

Le gestionnaire BI & IA, Données & Analytique est responsable de la stratégie, de la livraison et de l’excellence opérationnelle des capacités de Business Intelligence, de données et d’analytique avancée dans un modèle opérationnel TI de type Plan–Build–Run–Secure (PBRS).

Le titulaire du poste assure que les initiatives de données, BI et intelligence artificielle sont bien planifiées, efficacement livrées, sécurisées et continuellement améliorées en collaboration avec les parties prenantes TI et d’affaires.

Ce rôle combine leadership d’équipe, gouvernance technique et alignement stratégique afin de permettre une prise de décision basée sur les données à l’échelle de l’organisation.

Responsabilités:

Leadership stratégique & planification (Plan)

  • Définir la vision, la feuille de route BI, données et analytique
  • Aligner les initiatives avec la stratégie d’entreprise
  • Prioriser les investissements avec les parties prenantes clés
  • Promouvoir la valorisation des données, leur réutilisation et la standardisation
  • Développer les compétences de l’équipe et assurer la relève

Livraison de solutions & innovation (Build)

    • Superviser la livraison de projets BI, intégration de données et IA
    • Assurer la qualité des solutions :
      • Visualisation et rapports BI
      • Pipelines de données
      • Cas d’usage IA et analytique avancée
    • Favoriser l’innovation tout en respectant les standards d’entreprise
    • Collaborer avec les équipes applicatives

    Opérations & performance des plateformes (Run)

    • Garantir la stabilité et la performance des plateformes BI et données
    • Supporter les opérations (incidents, accès, continuité)
    • Standardiser les outils et améliorer la maturité opérationnelle
    • Optimiser les environnements hybrides (sur site et cloud)

    Sécurité, cycle de vie & évolution (Secure)

    • Assurer la sécurité des données et le contrôle des accès
    • Gérer le cycle de vie des applications et modernisation
    • Maintenir la continuité des rapports lors de migrations
    • Réduire la dette technique et améliorer la maturité analytique

    Habiletés, connaissances et aptitudes:

    • Leadership et gestion d’équipe
    • Forte capacité stratégique et analytique
    • Expérience BI, données, IA et machine learning
    • Connaissance des architectures de données modernes
    • Excellentes compétences en communication
    • Expérience avec cadres ITSM et modèles opérationnels (PBRS)

    Expérience:

    • 8-10 ans en BI, données ou analytique
    • 3-5 ans en gestion d’équipe
    • Expérience avec environnements hybrides (cloud et sur site)

    Scolarité:

    • Baccalauréat en informatique, analytique, ingénierie ou domaine connexe
    • Formation en gestion ou certification pertinente (atout)