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Junior Ai Engineer Jobs in Quebec (NOW HIRING)

Mentor junior developers through technical leadership, code reviews, and knowledge sharing * Contribute to AI standards, reusable components, and development practices that support CIMA+'s long-term ...

We sit at the intersection of consulting, data science, AI technologies, data engineering, and ... You will also help junior scientists grow. * Translate business and marketing challenges into ...

... junior members of the development team. - Conduct code reviews to ensure code quality ... GitHub Copilot, Claude, Cursor or ChatGPT) Familiarity with AI directed prompt engineering for ...

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Junior Ai Engineer information

What is a Junior AI Engineer?

A Junior AI Engineer is an entry-level professional who assists in the development and implementation of artificial intelligence models and systems. They typically work under the supervision of more experienced engineers to build, test, and deploy machine learning models, process data, and write code. Junior AI Engineers often collaborate with data scientists and software developers to integrate AI solutions into products or services. Their role is ideal for those with foundational knowledge in programming, mathematics, and machine learning concepts, looking to gain hands-on experience in the AI field.

What are the key skills and qualifications needed to thrive as a Junior AI Engineer?

To thrive as a Junior AI Engineer, you need a solid understanding of programming (especially Python), mathematics (linear algebra, statistics), and foundational machine learning concepts, often supported by a relevant degree or coursework. Familiarity with tools such as TensorFlow, PyTorch, and version control systems like Git is typically required, along with knowledge of cloud platforms like AWS or Azure. Strong problem-solving skills, willingness to learn, and effective teamwork and communication abilities help you stand out in this collaborative, fast-evolving field. These skills ensure you can contribute to AI projects efficiently, adapt to new technologies, and work well within multidisciplinary teams.

What are some typical challenges a Junior AI Engineer might face during their first year on the job?

As a Junior AI Engineer, you may encounter challenges such as understanding complex codebases, adapting to rapidly evolving AI frameworks, and balancing the need for innovation with production-level code quality. Collaborating with data scientists, senior engineers, and product managers to align on project goals and deliverables can also be a learning curve. Additionally, managing large datasets and debugging machine learning models require strong problem-solving skills and attention to detail, but these challenges offer excellent opportunities for growth and mentorship within your team.

What is the difference between Junior Ai Engineer vs Data Scientist?

AspectJunior Ai EngineerData Scientist
Required CredentialsBachelor's in CS, AI, or related field; some certificationsBachelor's or higher in CS, Statistics, or related; advanced certifications
Work EnvironmentDevelopment, coding, model implementationData analysis, modeling, insights generation
Employer & Industry UsageTech companies, startups, AI-focused firmsTech, finance, healthcare, research institutions

Junior Ai Engineers focus on developing and implementing AI models, often working closely with data and algorithms. Data Scientists analyze data to extract insights and build predictive models. While both roles require programming skills and a background in data or AI, Junior Ai Engineers are more involved in the technical development of AI systems, whereas Data Scientists focus on data analysis and interpretation.

What are the most commonly searched types of Ai Engineer jobs in Quebec?

The most popular types of Ai Engineer jobs in Quebec are:

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

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

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

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

What cities in Quebec are hiring for Junior Ai Engineer jobs?

Cities in Quebec with the most Junior Ai Engineer job openings:

Infographic showing various Junior Ai Engineer job openings in Quebec as of August 2026, with employment types broken down into 78% Full Time, 19% Part Time, and 3% Contract. Highlights an 68% Physical, 4% Hybrid, and 28% Remote job distribution.

AI & Agentic Engineer, Senior

LinkedIn Job Wrapping

Montreal, QC โ€ข On-site

Full-time

Medical, Dental, Vision, Retirement, PTO

Posted 5 days ago


Job description

Artefact is a next-generation data and AI consulting firm dedicated to accelerating the adoption of data and AI to create measurable business impact across the full enterprise value chain.

We sit at the intersection of consulting, data science, AI technologies, data engineering, and digital transformation. We do not just advise - we build, implement, and deliver results our clients can measure. Our teams bring together consultants, data scientists, data engineers, AI engineers, analysts, and digital experts to solve complex business challenges with pragmatic, production-ready solutions.

As Artefact continues to grow globally, we are building a team of entrepreneurial data and AI talent who can help clients move beyond experimentation and into scalable, governed, value-generating AI adoption.

The Role

Artefact is looking for a Senior AI & Agentic Engineer: a full-stack engineer who takes AI features from idea to production.

You will design and build the interfaces, services, and agentic systems at the heart of our client work, such as conversational applications over enterprise data, multi-step agents that automate business workflows, and the retrieval and data pipelines that support them. You will own your components end to end: the React front end, the Python or Node service behind it, the RAG pipeline feeding it, and the evaluations proving it works.

This role combines breadth and depth: the ability to take a feature from front end to cloud deployment, together with strong expertise in at least one major AI platform - Google (Gemini), Anthropic (Claude), or OpenAI.

You will work with direct client exposure, and you will support the professional development of the junior engineers around you.

What You'll DoBuild Full-Stack AI Applications, End to End

You will build AI products across the entire stack, from interface to infrastructure.

  • Develop user-facing interfaces in TypeScript/React and the backend services and APIs behind them in Python or Node.
  • Implement agentic behavior: orchestration, tool and function calling, memory, and guardrails.
  • Build retrieval-augmented generation (RAG) pipelines: ingestion, chunking, embeddings, vector and hybrid search.
  • Connect AI systems to enterprise data and applications via APIs, semantic layers, and protocols such as MCP.
Make AI Systems Production-Grade

Our standard is production quality: systems that are reliable, monitored, and maintainable.

  • Write evaluation suites and regression tests for LLM-powered features, and monitor cost, latency, and quality in production.
  • Apply solid engineering practice: version control, code review, automated testing, CI/CD, and observability.
  • Deploy on cloud infrastructure (GCP, Azure, or AWS) using containers, serverless, and infrastructure-as-code.
  • Build and maintain the data pipelines that feed AI systems, across warehouses, lakehouses, and vector stores.
Work AI-Natively and Client-Facing

Our engineers work AI-natively and represent Artefact directly with clients.

  • Use agentic coding tools (Claude Code, Gemini CLI, Codex, Cursor) daily, with good judgment about verification and review.
  • Communicate progress, trade-offs, and blockers clearly to clients and project leads.
  • Support pre-sales when needed: scope solutions, build demos, and estimate effort with our partnership and consulting teams.
  • Mentor junior engineers and contribute to internal accelerators, reusable components, and engineering standards.
What We're Looking ForRequired Experience
  • 3-5 years of experience in software engineering or data engineering, with extensive hands-on use of AI tools and LLM-based development over the past year (professional projects, internal initiatives, or substantial personal builds).
  • Professional English proficiency mandatory. You will work daily with international clients and colleagues.
  • Strong programming skills in Python and TypeScript/JavaScript, and experience building and consuming APIs.
  • Experience with front-end development (React or similar) and at least one backend framework.
  • Hands-on experience with RAG, embeddings, and vector search, and with at least one agentic framework (LangGraph/LangChain, Google ADK, Claude Agent SDK, or OpenAI Agents SDK).
  • Specialization in at least one major AI platform ecosystem - Google (Gemini, Vertex AI, Gemini Enterprise), Anthropic (Claude, Managed Agents, MCP), or OpenAI (Responses API, AgentKit) - and working experience with one cloud platform (GCP, Azure, or AWS).
  • Fluency with agentic coding tools such as Claude Code, Gemini CLI, Codex, or Cursor.
  • Experience building and maintaining data pipelines.
  • Bachelor's or Master's degree in computer science, engineering, or a related field, or equivalent practical experience.
Certifications

A certification on at least one major AI platform or cloud is a strong differentiator at application. If you do not hold one yet, obtaining one within your first 2 months in the role is a requirement - Artefact sponsors the exam and gives you time to prepare.

  • Examples: Claude Certified Developer - Foundations (Anthropic), Google Cloud Professional Machine Learning Engineer, Google Cloud Generative AI Leader, Microsoft Azure AI Engineer Associate, or equivalent AWS credentials.
Preferred Experience
  • Experience with MCP servers, multi-agent patterns, or LLM evaluation tooling (LangSmith, Langfuse, promptfoo).
  • Experience with Terraform or CI/CD pipelines.
Key Capabilities

A strong candidate will bring:

  • Breadth across the full stack, with depth in at least one AI platform
  • Owns features end to end, from interface to infrastructure
  • Cares about evaluation and reliability, not just the happy path
  • Communicates clearly in demos, documents, and code review
  • Client-facing mindset: understands client needs and translates business requirements into technical solutions
  • Learns new tools and models fast, and shares what works
Why Join Artefact

At Artefact, data and AI are not abstract strategy topics. They are tools for creating business value, improving organizations, and helping people make better decisions.

You will join a global community of data and AI experts who combine consulting, engineering, data science, marketing, and technology expertise. You will work on complex, high-impact problems with leading organizations and help shape how enterprises adopt AI responsibly and effectively.

We value action, collaboration, learning, client trust, and shared knowledge. We believe that technology only matters when it is used, adopted, and translated into impact.

Our values aren't decorations on a wall - they're how we actually work:

  • There is always a wayย - We're builders and problem-solvers. An idea only counts if it gets executed.
  • Client trust is won in the fieldย - We show up, sleeves rolled up, working side by side with our clients.
  • If it's not used, it's uselessย - We build for adoption and impact, not for slide decks.
  • If it's not shared, we're not doneย - Knowledge shared compounds. We invest in each other's growth.
  • We learn every dayย - In a field that moves this fast, standing still means falling behind. We embrace the challenge.

How We Support Our People

In addition to our values-driven culture, we offer a range of benefits and programs designed to support our employees' growth and well-being, including:

  • Learning and Development:ย Work alongside a multidisciplinary team of AI, data, and consulting experts who are committed to continuous learning, knowledge sharing, and professional growth.
  • Hybrid Flexibility:ย Our hybrid work model gives you the flexibility to balance collaboration, client needs, and personal commitments.
  • Comprehensive Benefits:ย We offer a competitive benefits package that includes medical, dental, and vision coverage, a 401(k) plan with company matching, and paid parental leave.
  • Time to Recharge:ย We believe sustainable performance matters. That's why we offer unlimited paid time off, giving you the flexibility to take the time you need.
  • Growth Opportunities:ย As a rapidly growing organization, you'll have the opportunity to expand your skills, take on new challenges, and help shape the future of the company.