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Generative Ai Testing Jobs in Quebec (NOW HIRING)

Agentic Engineer, Innovation

Montreal, QC

  • Medical

  • Dental

  • Vision

  • Life

  • Retirement

  • PTO

Build predictive, generative, and agentic AI solutions using sound machine learning, evaluation ... Operationalize AI solutions with testing, observability, monitoring, reliability controls ...

New

Junior Machine Learning Engineer

Montreal, QC · On-site

CA$80K - CA$95K/yr

  • Medical

  • Dental

  • Vision

  • Life

  • Retirement

  • PTO

Participate in code reviews, technical documentation, testing, and quality assurance activities. * Stay current with emerging trends in machine learning, generative AI, LLMs, deep learning, and cloud ...

... testing Generative AI solutions or LLM based systems Experience working in complex enterprise environments or large scale systems Qualifications Bachelor's Degree in Computer Science, Engineering ...

Java Spark Developer

Montreal, QC

  • Medical

  • Dental

  • Vision

  • Life

  • Retirement

  • PTO

Participate in testing and validation of AI-enabled workflows and solutions. Collaborate with teams exploring generative AI and intelligent automation use cases. Collaboration & Leadership ...

New

... testing. * Maintain product direction and priorities aligned with the broader business goals ... Experience with AI-enhanced products including generative AI is preferred. * Knowledge of product ...

... generative AI) within the platform. * Ensure platform scalability and uptime for high-volume ... Automated testing frameworks: Playwright * Identity and access management: OAuth 2.0, Role-Based ...

... testing. * Maintain product direction and priorities aligned with the broader business goals ... Experience with AI-enhanced products including generative AI is preferred. * Knowledge of product ...

Showing results 41-55

Generative Ai Testing information

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 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 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 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 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:

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 Prompt Engineer (AI Clinical Products)

Medfar

Montreal, QC • On-site, Remote

Full-time

Medical, PTO

Re-posted 17 days ago


Job description

Company Description

MEDFAR Clinical Solutions was founded in 2010 by two aeronautical engineers who realized that the healthcare system was not exploiting the full potential of technology. Supported by a large community of medical experts and focused on clinical success and patient safety, MEDFAR was the first company to certify a cloud-based Electronic Medical Record in Canada: MYLE (Make Your Life Easy).

Committed to promoting excellence and effectiveness in healthcare worldwide, MEDFAR differentiates itself by offering a unique healthcare management solution for clinics, which replaces inefficient processes with a faster and safer technological alternative.

Job Description

As a Senior Prompt Designer, you will play a defining role in shaping the quality, reliability, and evolution of MEDFAR's generative AI features — most notably CoeurWay, our AI-powered clinical scribe, and emerging AI capabilities within MYLE EMR. Reporting to the Director of UX, you will sit at the intersection of product, clinical quality, and AI craft, working closely with product designers, developers, QA, and client-facing teams to ensure that every AI-generated output meets the high standards required in a healthcare setting.

This is a senior individual contributor role with a clear growth path toward mentoring and leading a prompt engineering practice as MEDFAR's AI product surface expands.

Main Responsibilities

  • Audit and re-architect CoeurWay's existing monolithic prompts into a modular chain of focused, maintainable prompts — improving robustness, debuggability, and adaptability.

  • Lead the selection, evaluation, and pairing of language models to specific prompt tasks, fostering a model-agnostic approach that reduces vendor dependency and optimizes for quality and cost.

  • Own the quality of AI-generated clinical outputs: define what "good" looks like, identify failure modes, and drive continuous improvement through structured validation processes.

  • Evolve and re-align our existing evaluation framework, currently covering 7 clinical note quality rubrics, improving its coverage, automation potential, and alignment with clinical ground truth.

  • Establish and maintain a systematic approach to output validation, including edge case identification, regression testing for prompt changes, and documentation of known limitations.

  • Design and implement new prompts and evaluation suites to support new features in CoeurWay and MYLE EMR.

  • Collaborate with the GenAIOps to ensure prompts are production-ready — observable, versioned, and deployable through established CI/CD processes.

  • Develop a deep understanding of clinical workflows and the needs of healthcare providers, maintaining close relationships with client-facing teams and end users.

  • Stay current on the rapidly evolving LLM landscape — new models, prompting techniques, evaluation methodologies — and bring relevant findings back to the team.

  • Contribute to internal documentation, standards, and best practices for prompt engineering at MEDFAR.

  • Mentor future prompt designers as the team grows, and participate in hiring decisions as the practice scales.

Working conditions:

  • Contract: Permanent, full time (40h/week)

  • Working mode: Hybrid or remote

    • Occasional in-office presence may be required during the year (for events or team meetings, for example).

    • Candidates must reside in the province of Quebec.

Qualifications

Contribute with your strengths:

  • 5+ years of professional experience in AI/ML, product development, computational linguistics, or a closely related field.

  • 2+ years of hands-on prompt engineering experience in production LLM systems, ideally in a B2B SaaS or regulated industry context.

  • Demonstrable experience decomposing complex prompts into modular, chained architectures (e.g., using patterns such as prompt chaining, routing, reflection, or tool use).

  • Experience designing or significantly improving LLM evaluation frameworks — rubric design, inter-rater alignment, and failure mode analysis.

  • Strong familiarity with frontier commercial LLM APIs (OpenAI, Anthropic, Google, etc.) and the practical tradeoffs between them.

  • Experience working within or alongside healthcare, clinical, or life sciences domains is a strong asset.

  • Proficiency in Python or another scripting language for building eval pipelines or prompt tooling is an asset.

  • Experience with self-hosted or open-weight models is an asset.

  • Advanced proficiency in English, both written and spoken;

  • French is also required due to frequent client interactions

.

Who you are:

  • You understand that great prompt engineering is as much about thinking clearly as it is about technical execution. You break complex problems into focused, well-scoped sub-problems.

  • You are model-agnostic in mindset: you care about output quality and understand that the best tool for a task may not be the most popular or most expensive one.

  • You take clinical accuracy seriously. You appreciate that in a healthcare context, the quality bar is not just about user experience — it has direct implications for patient safety.

  • You are comfortable operating in ambiguity and iterating quickly, while maintaining rigorous documentation of what you've tried and why.

  • You are a strong collaborator who can communicate nuanced AI quality concepts to non-technical stakeholders, clinical users, and developers alike.

  • You have the seniority and judgment to work with significant autonomy, while knowing when to align and escalate.


Additional Information
  • Remote work and flexibility (supporting work-life balance)

  • RRSP contribution

  • Healthcare insurance from day one

  • Paid time off: 3 weeks + 1 additional week between Christmas and New Year

  • Annual training allowance to support your professional development

  • An onboarding program to help you get familiar with our environment and the digital healthcare field

  • All IT equipment is provided, with additional gear if needed

  • Internal growth opportunities (promotions, internal mobility)

  • Support from a wellness and social committee, with initiatives to foster team cohesion, mental health, and employee well-being

  • A company culture focused on transparency, collaboration, and innovation

  • Join a dynamic and innovative environment where your work has a real and wide-reaching impact, helping to modernize healthcare in Canada and internationally

With offices around the world, fluency in both French and English is a must at MEDFAR. Because of the need to communicate with colleagues and/or customers in other provinces or countries, bilingualism enables us to communicate in both languages while promoting the use of French. 

At MEDFAR, we value diversity, equity and inclusion within our team. We are committed to providing a work environment where every individual feels respected and supported, regardless of their background, identity or abilities.As part of our commitment to a fair and inclusive recruitment process, we offer accommodation to candidates who request it. If you need accommodation during your interview, please let us know so that we can provide you with an adapted experience.

MEDFAR has voluntarily subscribed to an Equal Employment Opportunity Program (EEOP). We encourage applications from women, visible minorities, ethnic minorities, aboriginal peoples and people with disabilities. When applying, we invite you to complete this section, which enables us to implement our Equal Employment Opportunity Program (EEOP). Self-identification is not compulsory, but may enable you to benefit from hiring or promotion measures if you have the skills required for the job.

To better understand the self-identification process, please consult this guide.