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Generative Ai Testing Jobs in Quebec (NOW HIRING)

Amgen

Engineer, AI Developer Platforms

Quebec, QC · On-site +1

... testing, secureuseand human review. What we expect of you We are all different, yet we all use our ... generative AI are a plus. * Hands-on experience writing code in at least one modern programming ...

KPMG

... testing, release, and sustainment * Strong communication skills with the ability to engage business ... Exposure to AI agent tools and generative AI capabilities such as Copilot Studio, Azure AI, Azure ...

KPMG

... testing, release, and sustainment * Strong communication skills with the ability to engage business ... Exposure to AI agent tools and generative AI capabilities such as Copilot Studio, Azure AI, Azure ...

Transat AT

Data Architect

Montreal, QC · On-site

... generative AI use cases. * Promote DataOps, DevOps, CI/CD, and MLOps practices, including automated testing, deployment, monitoring, and continuous improvement of data pipelines. * Collaborate with ...

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Generative Ai Testing information

What is the difference between Generative Ai Testing vs Data Scientist?

AspectGenerative Ai TestingData Scientist
Required CredentialsKnowledge of AI models, testing tools, programming skillsStatistics, programming, data analysis certifications
Work EnvironmentAI development teams, testing labs, tech companiesResearch labs, tech firms, finance, healthcare
Employer & Industry UsageAI product testing, quality assurance in techData analysis, predictive modeling across industries

Generative Ai Testing focuses on evaluating and validating AI-generated content and models, ensuring quality and accuracy. Data Scientists analyze data, build models, and derive insights. While both roles require programming and AI knowledge, Generative Ai Testing emphasizes testing processes, whereas Data Scientists focus on data analysis and model development.

How do I become a Generative AI Testing?

To become a Generative AI Tester, develop skills in machine learning, natural language processing, and programming languages like Python. Gain experience with AI frameworks such as TensorFlow or PyTorch and understand data quality and model evaluation techniques. Certifications in AI or data science can enhance your qualifications and improve job prospects.

Is Generative AI Testing a good career?

Generative AI Testing is a growing field within AI development that involves evaluating the quality and safety of AI-generated content. It requires skills in machine learning, programming, and understanding AI models, making it a promising career path with increasing demand as AI technologies expand. Professionals in this area can find opportunities in tech companies, research labs, and startups focused on AI innovation.

What are the key skills and qualifications needed to thrive as a generative AI testing specialist, and why are they important?

To thrive as a Generative AI Testing Specialist, you need a robust understanding of machine learning principles, model evaluation techniques, and a background in computer science or a related field. Familiarity with tools such as Python, TensorFlow, PyTorch, and model evaluation frameworks, as well as experience with automated testing platforms, is typically required. Analytical thinking, attention to detail, and strong communication skills help you identify model weaknesses and collaborate effectively with development teams. These skills are crucial to ensure the reliability, safety, and ethical deployment of generative AI solutions.

What are some common challenges faced when testing generative AI models, and how can I prepare to address them in this role?

Testing generative AI models often involves unique challenges such as evaluating the quality and relevance of generated content, detecting bias or inappropriate outputs, and ensuring model consistency across various prompts. You may work closely with data scientists and engineers to create robust evaluation frameworks and develop automated as well as manual testing strategies. Familiarity with prompt engineering, statistical evaluation techniques, and domain-specific knowledge will help you address these challenges effectively. Proactively staying updated on industry best practices and collaborating with cross-functional teams are key to success in this dynamic field.

What is generative AI testing?

Generative AI Testing refers to the process of evaluating and validating AI systems, particularly those that generate content such as text, images, or code. This type of testing focuses on assessing the accuracy, reliability, fairness, and safety of generative models to ensure they function as intended and avoid producing harmful or biased outputs. Testers use various methods, including automated and manual techniques, to check for issues like hallucinations, inappropriate content, or security vulnerabilities. The goal is to build trust in generative AI systems and ensure they meet quality and ethical standards before deployment.

What job categories do people searching Generative Ai Testing jobs in Quebec look for?

The top searched job categories for Generative Ai Testing jobs in Quebec are:

Generative Ai Testing jobs near you
Infographic showing various Generative Ai Testing job openings in Quebec as of August 2026, with employment types broken down into 1% As Needed, 86% Full Time, 9% Part Time, 3% Contract, and 1% Nights. Highlights an 88% Physical, 2% Hybrid, and 10% Remote job distribution.

Senior Consultant - Copilot Studio / Agentic developer

KPMG

Montreal, QC • On-site

Full-time

Re-posted 16 days ago

Job description

Overview

At KPMG in Canada, our people bring their unique perspectives to Canada’s most important challenges. Here, you can build momentum that reaches beyond our business, develop skills for the future, and take ownership of your career with support at every stage. Join a firm where your career can make a difference.

We are looking for a Senior Consultant – Agentic AI and Copilot Development, who will act as a consultant, solution designer, and hands-on technical contributor to support our clients in the design, integration, and deployment of AI agents, business copilots, and intelligent automation solutions.

The successful candidate will bring together consulting experience, a strong understanding of business challenges, and practical expertise in generative and agentic AI platforms, including Microsoft Copilot Studio, Azure AI, ChatGPT, Claude, Perplexity, LLM APIs, orchestration frameworks, RAG, and enterprise integrations.


What you will do
  • Design, develop, and deploy AI agents, business copilots, and intelligent automation solutions, from prototype through to production.
  • Translate clients’ business needs into concrete, prioritized, and measurable use cases, taking into account expected value, existing processes, available data, and user adoption.
  • Facilitate functional and technical workshops to gather requirements, define user journeys, identify integration constraints, and document design decisions.
  • Work hands-on in configuring and developing solutions using Copilot Studio, Power Platform, Azure AI, Azure OpenAI, ChatGPT Enterprise, Claude, Perplexity, APIs, Python, connectors, and cloud services.
  • Design pragmatic agentic architectures including specialized agents, task orchestration, human-in-the-loop workflows, knowledge bases, RAG, tool calling, connectors, guardrails, and escalation mechanisms.
  • Integrate agents and copilots with enterprise applications, data sources, APIs, collaboration platforms, document management systems, CRM, ERP, and cloud environments.
  • Collaborate with architects, developers, business analysts, data experts, security, risk, and compliance teams to deliver robust, secure, and client-adapted solutions.
  • Produce high-quality consulting deliverables: solution designs, functional and technical documentation, implementation plans, backlogs, test scenarios, user guides, and evolution recommendations.
  • Contribute to the development of KPMG assets related to agentic AI: demos, accelerators, solution patterns, delivery approaches, estimates, and client presentation materials.
  • Remain hands-on and pragmatic: resolve blockers, test solutions, refine prompts and workflows, challenge technical decisions, and ensure delivered solutions create tangible business value.
  • Participate in advisory and business development activities: opportunity qualification, proposal preparation, effort estimation, and delivery of demonstrations or prototypes.

What you bring to the role
  • At least 3 years of experience in consulting, technology delivery, solution development, application integration, intelligent automation, or digital transformation.
  • Experience in a consulting firm or client-facing professional services environment, with a demonstrated ability to understand client needs and deliver in demanding contexts.
  • 2 to 3 years of hands-on experience with generative AI solutions, AI agents, copilots, conversational AI, intelligent automation, or related platforms.
  • Practical proficiency with at least part of the Microsoft ecosystem, including Copilot Studio, Microsoft 365 Copilot, Azure AI, Azure OpenAI, Power Platform, Dataverse, Teams, SharePoint, Graph, or Microsoft connectors.
  • Experience with generative AI platforms and tools beyond Microsoft, such as ChatGPT Enterprise, Claude, Perplexity, LangChain, LangGraph, LlamaIndex, CrewAI, vector databases, LLM APIs, or orchestration frameworks.
  • Hands-on experience in solution design and development, including Python, REST APIs, system integration, RAG, prompt engineering, testing, version control, documentation, and deployment.
  • Strong understanding of security, permissions, data governance, privacy, compliance, monitoring, and lifecycle management of AI solutions in an enterprise context.
  • Ability to work with both business and technical stakeholders, simplify complex AI concepts, and translate functional needs into concrete solutions.
  • Experience in agile or iterative delivery, including backlog management, client demonstrations, user testing, prioritization, and continuous improvement.
  • Excellent written and verbal communication skills in both French and English, with the ability to produce clear documentation, actionable recommendations, and high-quality consulting-level presentations.

This position requires written and oral fluency in English because it involves interpretation and application of English standards, guidance, laws and regulations, servicing of English-speaking clients located across Canada and collaboration with English Speaking colleagues located outside of Quebec. 

Providing you with the support you need to be at your best


Our Values, The KPMG Way

Integrity, we do what is right | Excellence, we never stop learning and improving | Courage, we think and act boldly | Together, we respect each other and draw strength from our differences | For Better, we do what matters

KPMG in Canada is a proud equal opportunities employer and we are committed to creating a respectful, inclusive and barrier-free workplace that allows all of our people to reach their full potential. A diverse workforce is key to our success and we believe in bringing your whole self to work. We welcome all qualified candidates to apply and hope you will choose KPMG in Canada as your employer of choice.

Adjustments and accommodations throughout the recruitment process

At KPMG, we are committed to fostering an inclusive recruitment process where all candidates can be themselves and excel. We aim to provide a positive experience and are prepared to offer adjustments or accommodations to help you perform at your best. Adjustments (informal requests), such as extra preparation time or the option for micro breaks during interviews, and accommodations (formal requests), such as accessible communication supports or technology aids, are tailored to individual needs and role requirements. You will have an opportunity to request an adjustment or accommodation at any point throughout the recruitment process. If you require support, please contact KPMG’s Employee Relations Service team by calling 1-888-466-4778.

AI Usage

Weembrace the use of artificial intelligence (AI) to enhance the candidate experience and streamline our recruitment processes. AI tools may help with organizing applications or surfacing relevant qualifications. However, no hiring decisions are made using AI. Every hiring decision is made by our hiring managers and recruitment professionals, who are equipped with training that empowers them to use these tools responsibly. AI technologies used in our recruitment process undergo detailed risk assessments, including security and privacy requirements, that align with KPMG’s Trusted AI framework.

We believe technology should empower human judgment, not replace it. It’s one of the many ways we’re delivering on our vision of being a technology-first, people-driven firm.

Qualifications:
  • At least 3 years of experience in consulting, technology delivery, solution development, application integration, intelligent automation, or digital transformation.
  • Experience in a consulting firm or client-facing professional services environment, with a demonstrated ability to understand client needs and deliver in demanding contexts.
  • 2 to 3 years of hands-on experience with generative AI solutions, AI agents, copilots, conversational AI, intelligent automation, or related platforms.
  • Practical proficiency with at least part of the Microsoft ecosystem, including Copilot Studio, Microsoft 365 Copilot, Azure AI, Azure OpenAI, Power Platform, Dataverse, Teams, SharePoint, Graph, or Microsoft connectors.
  • Experience with generative AI platforms and tools beyond Microsoft, such as ChatGPT Enterprise, Claude, Perplexity, LangChain, LangGraph, LlamaIndex, CrewAI, vector databases, LLM APIs, or orchestration frameworks.
  • Hands-on experience in solution design and development, including Python, REST APIs, system integration, RAG, prompt engineering, testing, version control, documentation, and deployment.
  • Strong understanding of security, permissions, data governance, privacy, compliance, monitoring, and lifecycle management of AI solutions in an enterprise context.
  • Ability to work with both business and technical stakeholders, simplify complex AI concepts, and translate functional needs into concrete solutions.
  • Experience in agile or iterative delivery, including backlog management, client demonstrations, user testing, prioritization, and continuous improvement.
  • Excellent written and verbal communication skills in both French and English, with the ability to produce clear documentation, actionable recommendations, and high-quality consulting-level presentations.

This position requires written and oral fluency in English because it involves interpretation and application of English standards, guidance, laws and regulations, servicing of English-speaking clients located across Canada and collaboration with English Speaking colleagues located outside of Quebec. 

Providing you with the support you need to be at your best

Education:UNAVAILABLEEmployment Type: FULL_TIME

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