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Added 2 months ago
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Consultant/Senior Consultant, Credit Risk Models - Financial Engineering & Modeling (Perm/Contract)
Deloitte
Toronto, ON
- Full-time
…benchmark model using Python or R by leveraging statistics, machine learning and artificial intelligence, or translate complex analyses into clear recommendations for senior stakeholders.…
Added 2 months ago
Solutions Delivery Intern, Maintenance Domain, (Winter/ January 2027, 12 Months)
Internship List
Oakville, ON
…billions of data points a day, Geotab leverages data analytics and machine learning to improve productivity, optimize fleets through the reduction of fuel consumption, enhance driver safety…
Added 3 months ago
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Senior Software Developer (Digital Workflow) / Développeur(-euse) sénior, logiciel
Vention
Montreal, QC
- Full-time
…who grow through meaningful work, solving complex challenges, learning fast, and seeing the results of our efforts every…
Added 2 months ago
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Actuarial Senior Consultant, Life & Health
Deloitte
Kitchener, ON
- Full-time
Stay current with technical and industry developments including Insurtech, Artificial Intelligence / Machine Learning, Generative AI and Advanced Analytics.
Added 2 months ago
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Manager, Credit Risk Models - Financial Engineering & Modeling
Deloitte
Toronto, ON
- Full-time
…benchmark model using Python or R by leveraging statistics, machine learning and artificial intelligence, or translate complex analyses into clear recommendations for senior stakeholders.…
Added 2 months ago
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Director, Engineering (Ad Tech)
Fox Corporation
Toronto, ON · CAN - ON - Yonge St
- Full-time
Build and develop a high-performing engineering organization by coaching managers and senior engineers, growing staff-level leadership, and creating clarity in roles, expectations, and…
Added 2 months ago
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Senior Software Developer
Taiv
Winnipeg, MB
- Full-time
Strong understanding of performance critical video and machine learning pipelines
Added 2 months ago
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Oliver Wyman - Operations Supply Chain –Engagement Manager
Oliver Wyman
Toronto, ON
- Full-time
…toolkit, including artificial intelligence-driven tools, like our machine learning-based forecasting platform. We combine this with our deep project expertise and proven methods and…
Added 2 months ago
Solutions Architect
Appnovation Technologies
Toronto, ON
…from mobile and web applications to advanced analytics and machine learning, to content and engagement management service enablement…
Added 2 months ago
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Human Resources Business Partner
GFL Environmental Inc.
Brampton, ON · Hamilton, ON · Mississauga, ON · Niagara Falls, ON
- Full-time
Must have experience working in a Unionized environment
Added 2 months ago
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Data Scientist
Symbiotic Digital
Toronto, ON · Queen's Park Ontario Provincial Government, Ontario
- Contract
statistical analysis, machine learning methodologies, and modern data analytics
Added 2 months ago
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Senior Technical Account Manager (Strategic Accounts & Partnerships)
Sanctuary AI
Vancouver, BC
- Full-time
…teleoperation and demonstration data become policies, what imitation learning and behavior cloning do and do not solve today, and where the capability boundary…
Added 2 months ago
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Prototype Technician
CURA
Calgary, AB
- Full-time
…entrepreneurial culture that values collaboration, creativity, learning and…
Added 2 months ago
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Information Security Specialist (Security Posture Insights, Reporting and Remediation)
TD
Toronto, ON
- Full-time
…signals and remediation recommendations. The role reports to the Senior Manager, Security Compliance and Operations Management and works across infrastructure security governance, security…
Added 3 months ago
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Staff Data Engineer
Tilt (f.k.a. Delphia)
Remote, Canada
- $210,000 to $270,000 CAD / year
- Full-time
- Remote
Design data models that support product development, machine learning, and long-term platform evolution.
Added 2 months ago
V
Senior Software Developer (Digital Workflow) / Développeur(-euse) sénior, logiciel
Vention
Montreal, QC
- Full-time
…who grow through meaningful work, solving complex challenges, learning fast, and seeing the results of our efforts every…
Added 2 months ago
Senior Consultant - Fraud Analytics
EY
Toronto, ON
To qualify for the role you must have
Added 2 months ago
Director, AI & Data Science
Artefact
Montreal, QC
You will lead a team of AI & machine learning engineers and managers, driving the design and delivery of production-grade AI solutions - from classical machine learning models to…
Added 2 months ago
Director, AI & Agentic Engineering
Artefact
Montreal, QC
You will lead a team of AI & machine learning engineers and managers, driving the design and delivery of production-grade AI solutions - from classical machine learning models to…
Added 2 months ago
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Senior Software Engineer, AI
Calabrio
Canada
- Full-time
Calabrio-Verint is looking for a highly skilled and experienced Senior Software Engineer, AI to perform a key role in our digital transformation program, and deliver exceptional customer…
Added 2 months ago
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Manager, Customer Analytics (Sales & Marketing)
Jobber
Remote, Canada
- Full-time
- Remote
…& Channels and Sales & Partnerships pods. Reporting to the Senior Manager, Customer Analytics, this leader will manage a team of analysts and partner closely with Directors, Senior…
Added 2 months ago
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Software Development Co-op
commonsku
Remote, Canada
- $3,500 to $4,800 CAD / month
- Full-time
- Remote
…with more experience. You ask questions, share what you’re learning, and contribute to a positive team environment. (Community…
Added 2 months ago
Senior Forward Deployed Engineer (Gemini Enterprise)
Artefact
Montreal, QC
Artefact is looking for a Senior Deployed AI Engineer specialized in Gemini Enterprise and the Google AI stack: an engineer who works embedded with our clients and takes AI products from…
Added 2 months ago
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Senior Design Verification Engineer
Cognichip
Toronto, ON
- $150,000 to $180,000 CAD / year
- Full-time
We operate on a hybrid schedule with four days in office, one day remote
Added 2 months ago
GD
Sr. Manager, Financial Planning & Analysis
Groupe Dynamite
Mont-Royal, QC
- Full-time
Generative AI (e.g., Claude, Copilot) and Machine Learning to improve data integrity and predictive forecasting accuracy;

Artefact

Senior Forward Deployed Engineer (Gemini Enterprise)

Montreal, QC, Canada

Apply on job-boards.greenhouse.io About employer

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Job details

Posting language: English
Posted: Sep 1, 2026

Original job description

About Artefact

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 Deployed AI Engineer specialized in Gemini Enterprise and the Google AI stack: an engineer who works embedded with our clients and takes AI products 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 front end, the service behind it, the data and retrieval pipelines feeding it, the deployment, and the evaluations proving it works.

This role combines deep, certified expertise in Google's enterprise AI stack (Gemini models, Vertex AI, and the Gemini Enterprise agent platform) with the ability to deliver end to end. Beyond your platform specialization, you will be expected to work confidently across the full delivery lifecycle - full-stack development, data engineering, cloud infrastructure, evaluation, and client communication.

You will work closely with our clients, with direct exposure from the start, and you will support the professional development of the engineers around you.

What You'll Do

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.
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.

Go Deep on Gemini Enterprise and the Google AI Stack

You will be the team's reference for Google's enterprise AI platform.

Design and build agents with Gemini models, Vertex AI, the Agent Development Kit (ADK), and Agent Engine.
Implement and configure Gemini Enterprise for clients: Agent Designer for natural-language and trigger-based agents, the Inbox for managing long-running agents at scale, and agent sandboxes for autonomous problem-solving.
Connect Gemini Enterprise to the client's application landscape through first-party and partner connectors, with proper permissions, governance, and auditability.
Build grounded, retrieval-backed applications with Vertex AI Search and RAG Engine, grounding with Google Search, and BigQuery as the data backbone.
Implement agent interoperability through the A2A protocol and MCP.
Track Google's releases closely and translate new capabilities into client value quickly.

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 For

Required 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).
Strong hands-on experience with the Google AI stack: Gemini models, Vertex AI, and ideally Gemini Enterprise or ADK - ideally with experience taking at least one solution to production on GCP.
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 (Google ADK, LangGraph/LangChain).
Strong working experience with GCP; Azure or AWS is a plus.
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 Google Cloud certification is a strong differentiator at application. If you do not hold one yet, obtaining it within your first 2 months in the role is a requirement - Artefact sponsors the exam and gives you time to prepare.

Google Cloud Professional Machine Learning Engineer (preferred), covering Vertex AI, generative AI, and production ML.
Google Cloud Generative AI Leader is valued as a foundation, complemented by hands-on Vertex AI / Gemini Enterprise delivery experience.

Preferred Experience

Experience with MCP servers, multi-agent patterns, or LLM evaluation tooling (LangSmith, Langfuse, promptfoo).
Experience with Terraform or CI/CD pipelines.
Experience with GCP, BigQuery, or Google Workspace integrations alongside Gemini Enterprise.

Key Capabilities

A strong candidate will bring:

Deep expertise in Gemini Enterprise and the Google AI stack, combined with breadth across the full stack
Owns features end to end, from interface to infrastructure
Cares about evaluation and reliability, not just the happy path
Communicates clearly with clients 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 way - We're builders and problem-solvers. An idea only counts if it gets executed.
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.
If it's not shared, we're not done - Knowledge shared compounds. We invest in each other's growth.
We learn every day - In a field that moves this fast, standing still means falling behind. We embrace the challenge.

Apply on job-boards.greenhouse.io About employer

More about this job

Responsibilities

You will design and build end-to-end AI products, including agentic systems, RAG pipelines, and user-facing interfaces. You will work embedded with clients to deploy production-grade AI solutions while maintaining high standards for reliability and performance.

Requirements

Candidates must have 3-5 years of experience in software or data engineering with extensive hands-on use of LLMs and the Google AI stack. A bachelor's or master's degree in a relevant field is required, along with strong proficiency in Python and TypeScript.

Skills

Gemini Enterprise
Vertex AI
Python
TypeScript
React
RAG
Agentic systems
Data engineering
Cloud infrastructure
GCP
API development
Machine learning
Software engineering
Prompt engineering
CI/CD
Vector search

Benefits

Professional development support
Certification sponsorship
Global team collaboration

Visa sponsorship

Not detected in the job text

Keywords

Gemini Enterprise
Vertex AI
Google Cloud Platform
Python
TypeScript
React
RAG
Agentic AI
BigQuery
Data Engineering
Machine Learning
LLM
API
Terraform
CI/CD
Vector Databases
Software Engineering
Consulting
Artificial Intelligence
Cloud Infrastructure
Prompt Engineering
LangGraph
LangChain
MCP
Observability
Containerization
Serverless
Data Pipelines
Governance
Auditability

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Jobs in Canada