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Genai Developer Jobs in Quebec (NOW HIRING)

Support GenAI initiatives from problem framing through production deployment and continuous ... Collaborate with data scientists, AI engineers, platform teams, and business stakeholders to ...

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Genai Developer information

What are the key skills and qualifications needed to thrive as a GenAI Developer, and why are they important?

To thrive as a GenAI Developer, you need a strong background in machine learning, deep learning frameworks (like TensorFlow or PyTorch), and programming languages such as Python, often supported by a degree in computer science or a related field. Familiarity with cloud platforms (AWS, Azure, GCP), APIs, and prompt engineering, as well as certifications in AI or ML, are typically used in this role. Creativity, problem-solving, and effective communication set outstanding GenAI Developers apart. These skills are crucial for building, optimizing, and deploying powerful generative AI models that address complex business challenges.

What are some common challenges GenAI Developers face when integrating generative AI models into existing products?

GenAI Developers often encounter challenges related to model deployment, scalability, and ensuring data privacy when integrating generative AI models into established products. Balancing the computational requirements of large AI models with real-time application demands can be complex, and optimizing inference speed without sacrificing model quality is a key consideration. Additionally, collaborating closely with product managers, data scientists, and DevOps teams is essential to align AI outputs with business goals and maintain robust, ethical AI practices.

What are GenAI Developers?

GenAI Developers are professionals who design, build, and optimize applications using generative artificial intelligence technologies. They work with models such as GPT, DALL-E, or Stable Diffusion to create tools for generating text, images, code, and other content. These developers need strong programming skills, a solid understanding of machine learning, and experience working with AI frameworks and APIs. Their responsibilities often include training custom models, integrating AI into products, and ensuring ethical use of generative AI solutions.

What is the difference between Genai Developer vs Machine Learning Engineer?

AspectGenai DeveloperMachine Learning Engineer
Required CredentialsBachelor's in CS, AI, or related; experience with NLP and AI frameworksBachelor's or higher in CS, Data Science, or related; strong programming and ML skills
Work EnvironmentDevelops AI models focused on generative AI, often in AI startups or tech companiesBuilds and deploys ML models across various industries, including tech, finance, healthcare
Employer & Industry UsagePrimarily in AI-focused companies, research labs, and tech firmsWidely used across industries like tech, finance, healthcare, and retail

While both roles involve AI and machine learning, Genai Developers specialize in creating generative AI models like chatbots and content generators, whereas Machine Learning Engineers develop a broader range of ML models for various applications. The roles overlap in skills and tools but differ in focus and industry applications.

Infographic showing various Genai Developer job openings in Quebec as of May 2026, with employment types broken down into 89% Full Time, 7% Part Time, 2% Temporary, and 2% Contract. Highlights an 73% Physical, 1% Hybrid, and 26% Remote job distribution.
Lead/Staff Full Stack Engineer, AI Platform & Agents (US/Canada Hybrid/Remote)

Lead/Staff Full Stack Engineer, AI Platform & Agents (US/Canada Hybrid/Remote)

Wolters Kluwer

Quebec, QC • On-site, Remote

Full-time

Medical, Dental, Vision, Retirement, PTO

Posted 16 days ago


Wolters Kluwer rating

8.8

Company rating: 8.8 out of 10

Based on 23 frontline employees who took The Breakroom Quiz

30th of 183 rated software companies


Job description

Build the GenAI platform that powers critical decisions in healthcare, legal, tax, and compliance industries. Your work will directly shape the future of these fields, enabling faster, safer, and more impactful decision-making at a global scale.

-Location: : US/Canada, Hybrid or Remote
-Work Hours: Must have 9-11 AM CST overlap

  • Candidates within commuting distance of a Wolters Kluwer office will be considered for hybrid employment, with 2 days per week onsite.
  • Candidates not within commuting distance will be considered for remote employment.

About this role

Our team is building a central GenAI Platform to empower hundreds of product teams across the organization with scalable capabilities for rapid development, validation, and deployment of AI agents. We also drive the development of the most impactful AI agents, ensuring faster delivery and greater impact across multiple domains. With over 20 agents already launched and many more in progress, our work accelerates innovation and improves outcomes in critical industries.

You'll join a 100-engineer remote-first team within a larger organization that combines the stability of an established company with the agility of a startup. In this high-autonomy, high-impact role, you'll take problems from concept to production. You'll design and ship full-stack systems, shape platform capabilities to empower hundreds of product teams, and directly contribute to the development of the most impactful AI agents.

Flagship Agent: UpToDate Expert AI

In Health, we're launchingUpToDate Expert AI-a medical research and clinical reasoning agent that transforms the world's most widely used pointofcare knowledge resource into a realtime medical assistant. Millions of physicians will rely on it to accelerate differential diagnosis, refine treatment decisions, and reduce cognitive load-while maintaining rigorous safety, privacy, and guideline fidelity. Improvements you ship (latency, reliability, hallucination reduction) will translate directly into faster, higher-quality patient care at global scale.

Tech stack

You don't need to know all of these on day one, but you should be ready to learn quickly.

  • TypeScript, Node.js, React, Python, LangChain/LangGraph, MCP/A2A, Rust
  • AWS (primary), Azure, GCP; Docker, Terraform, GitHub Actions
  • DocumentDB, DynamoDB, OpenSearch, Azure AI Search
  • Azure OpenAI, AWS Anthropic, Google Gemini
  • GitHub, Confluence, Slack

What you'll do

  • Design and implement fullstack applications, AI agents, and platform components that enable rapid GenAI agent development, validation, and deployment.
  • Build developer tooling, CI/CD, and observability for safe, fast iteration (evals, canaries, rollout/rollback, cost and quality telemetry).
  • Apply secure SDLC and privacybydesign practices (threat modeling, least privilege).
  • Collaborate with product, UX, and domain experts to deliver customerfocused solutions with measurable outcomes.
  • Apply current LLM patterns (RAG, retrieval, routing, tool-use, evals) to deliver measurable customer value-faster, more reliable AI systems; reduced time-to-decision; improved trust/safety metrics; and lower cost per query.
  • Lead by example through writing high-quality, maintainable code that demonstrates engineering craftsmanship.

Team context

  • Org and Sub-teams: Central GenAI Platform within Wolters Kluwer, driving innovation across businesses by creating re-usable platform services and components. Sub-teams are fewer than 10 engineers, focused on platform services or customer-facing agents.
  • Culture and Reporting: We value a "manager of one" mindset, where outcomes matter more than optics. Authority is earned through demonstrated impact, not tenure or title. You'll report directly to the VP of Engineering, AI Platform.
  • Team Size and Impact: Our globally distributed team of ~100 engineers combines the stability of an established company with the agility of a startup. We are moving fast, and there are many areas where you can have a big impact.
  • Work setup: Remote-first in US or EU, with hybrid options near major offices. Collaboration requires 9-11 AM CST overlap. Occasional travel for team onsites/offsites as needed.

Minimum qualifications

  • 5+ years of professional software engineering experience.
  • Strong fullstack development skills and cloud experience (AWS/Azure/GCP).
  • Expert in at least one, and proficient across the others:
    • AI Agent development and evaluation
    • Backend development
    • Frontend development
    • Cloud services (AWS/Azure/GCP)
    • CI/CD and Infrastructure as Code
    • Site Reliability Engineering (SRE)
    • Quality engineering / testing strategy
    • Secure SDLC and privacy by design
  • Proven track record delivering secure, reliable, cloudnative systems to production.
  • Excellent problemsolving, ownership, and crossfunctional communication.

Nice to have

  • Proven ability to deliver software products independently or as part of a small, fast-paced team.
  • Experience of taking AI agents from concept to production, including safety evaluations, iterative testing (e.g., A/B testing), and continuous improvement.
  • Experience with LangChain/LangGraph and MCP; vector/RAG systems; OpenSearch.
  • Worked on traditional ML tasks like training, deployment, and monitoring.
  • Understand how LLMs work, their failure modes, and techniques like fine-tuning and model adaptation.
  • Familiarity with regulatory frameworks such as SOC2, HIPAA, etc.

To apply:

Please submit your resume along with a brief cover letter that includes a "Statement of Exceptional Work." In your cover letter, highlight one of your most impactful projects by addressing the following:

  • Your role and the problem space you were working in
  • The technical and product challenges you faced, and how you addressed them
  • The measurable impact of your work (e.g., metrics, outcomes, improvements)

This will help us better understand your approach to solving complex problems and the value you bring to the team.

Please do not include any proprietary or confidential information in your submission

Our Interview Practices

To maintain a fair and genuine hiring process, we kindly ask that all candidates participate in interviews without the assistance of AI tools or external prompts. Our interview process is designed to assess your individual skills, experiences, and communication style. We value authenticity and want to ensure we're getting to know you-not a digital assistant. To help maintain this integrity, we ask to remove virtual backgrounds and include in-person interviews in our hiring process. Please note that use of AI-generated responses or third-party support during interviews will be grounds for disqualification from the recruitment process.

Applicants may be required to appear onsite at a Wolters Kluwer office as part of the recruitment process.

Compensation:

$97,400.00 - $174,050.00 USD

Compensation range listed is based on primary location of the position. Actual base salary offer is influenced by a wide array of factors including but not limited to skills, experience and actual hiring location. Your recruiter can share more information about the specific offer for the job location during the hiring process.

Additional Information:

Wolters Kluwer offers a wide variety of competitive benefits and programs to help meet your needs and balance your work and personal life, including but not limited to: Medical, Dental, & Vision Plans, 401(k), FSA/HSA, Commuter Benefits, Tuition Assistance Plan, Vacation and Sick Time, and Paid Parental Leave. Full details of our benefits are available upon request.


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