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. 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. 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.

Build

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. 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 valuable judgment about verification and review. Communicate progress, trade-offs, and blockers clearly to clients and project leads. 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. ~ 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.



A certification on at least one major AI platform or cloud is a strong differentiator at application.

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.

Experience with Terraform or CI/CD pipelines. Breadth across the full stack, with depth in at least one AI platform Communicates clearly in demos, documents, and code review Client‑facing mindset: understands client needs and translates business requirements into technical solutions 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. Client trust is won in the field — We show up, sleeves rolled up, working side by side with our clients.

If it's not used, it's useless — We build for adoption and impact, not for slide decks. We learn every day — In a field that moves this fast, standing still means falling behind.

How We Support Our People Learning and Development: Work alongside a multidisciplinary team of AI, data, and consulting experts who are committed to continuous learning, knowledge sharing, and professional growth.

Hybrid Flexibility: Our hybrid work model gives you the flexibility to balance collaboration, client needs, and personal commitments.

Comprehensive Benefits: 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: We believe sustainable performance matters.

Growth Opportunities: 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. #

📌 AI & Agentic Engineer, Senior (Montreal)
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📍 Montreal