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Added 2 mins ago
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Student Intern, Corporate Sustainability
Celestica
Toronto, ON
- $23 to $30 CAD / hour
- Temporary
With deep expertise in design, engineering, manufacturing, supply chain management and platform solutions, Celestica enables critical data center infrastructure for AI, cloud, and hybrid…
Added 2 mins ago
AC
Data Engineer - Snowflake, dbtCore/Cloud, AWS
Aviva Canada
Markham, ON
- Full-time
…platforms to build robust data pipelines and systems that power analytics and AI initiatives. In this role, you will contribute to the design and implementation of data solutions that…
Added 2 mins ago
OM
Sr. Campaign Manager, Social
Omnicom Media
Toronto, ON
- Full-time
Collaborate with strategy, planning, and analytics teams to align on objectives
Added 17 mins ago
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Senior Finance Analyst
TD
Toronto, ON
- Full-time
…priorities by delivering enterprise-wide technology, digital, and platform capabilities that support both Business Units and Corporate…
Added 17 mins ago
T
Product Control Analyst
TD
Toronto, ON
- Full-time
Added 17 mins ago
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Engineer I
TD
Mississauga, ON · Toronto, ON
- Full-time
TD Enterprise Protect Analytics Engineering Team is responsible for managing the bank's cyber security logging and monitoring systems, providing technical guidance and direction.
Added 17 mins ago
Senior Strategist
Ogilvy
Toronto, ON
…brands. Powered by exceptional talent and our agentic marketing platform WPP Open, WPP unites cutting-edge media intelligence and data solutions, creativity, production, enterprise…
Added 32 mins ago
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Engineer I
TD
Toronto, ON
- Full-time
TD Enterprise Protect Analytics Engineering Team is responsible for managing the bank's cyber security logging and monitoring systems, providing technical guidance and direction.
Added 32 mins ago
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Machine Learning Scientist
Swim Recruiting
Vancouver, BC · Greater Vancouver, BC
- $100,000 to $150,000 CAD / year
- Contract
Work alongside domain experts, data engineers, and platform teams who are deeply invested in making your models succeed in the real world. Small team culture means your contributions are…
Added 33 mins ago
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Sr. Campaign Manager, Social
Adelphi Group
Toronto, ON
- Full-time
· Collaborate with strategy, planning, and analytics teams to align on objectives
Added 47 mins ago
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Product Owner - Digital Enablement
Sanofi
Toronto, ON
- Full-time
Track value metrics post-release, interpret real user behavior (not just delivery velocity), and use cloud data platform and GenAI insights to adapt direction.
Added 1 hour ago
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Data Scientist
Raise
Calgary, AB
- Full-time
Supply Chain Management (SCM) Data, Innovation & Analytics is seeking an experienced Data Scientist with strong Databricks expertise to design, develop, and operationalize scalable Supply…
Added 1 hour ago
TB
Digital & eCommerce Specialist
The Beer Store
Bolton, ON
- Full-time
Leverage analytics, customer insights, and performance data to identify trends, measure success, and recommend improvements across digital and eCommerce channels
Added 1 hour ago
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Power BI & Azure Platform Engineer / Toronto, ON (Onsite) - FTE
AceStack
Toronto, ON
- Full-time
The role involves working across data engineering, analytics, platform administration, performance optimization, and migration from legacy Azure data platforms to Microsoft Fabric.
Added 1 hour ago
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Underwriting Manager, Middle Market Package
AXA XL
Toronto, ON
- Full-time
You will report to the Head of Middle Market Data Analytics and Product.
Added 1 hour ago
UO
Post Doctoral Associate, Immunology, DNA damage, and Apoptosis
University of Calgary
Calgary, AB
- Full-time
Added 1 hour ago
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Senior Business Program Analyst
TD
Toronto, ON
- Full-time
Bachelor’s degree in business, finance, analytics, mathematics, computer science, or a related field.
Added 1 hour ago
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Manager, Business Management
TD
Toronto, ON
- Full-time
Added 1 hour ago
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Java/Spring Boot Developer - Vice President
Citi
Mississauga, ON
- Full-time
Join the Equities Middle Office Technology team as a Senior Java/Spring Boot Developer, where you will be a key contributor for managing complex BAU deliverables while driving strategic…
Added 1 hour ago
VI
Manager, Yardi and Financial Systems
Vital Infrastructure Property Trust
Toronto, ON
- $110,000 to $130,000 CAD / year
- Full-time
…management, and ongoing stabilization of the Yardi Voyager platform and related Yardi products. This includes supporting approved business requirements across accounting, reporting,…
Added 1 hour ago
OG
Social Media Manager
Onni Group of Companies
Vancouver, BC
- Full-time
Develop and execute data-driven content strategies that increase brand awareness, audience engagement, and platform performance across key social channels
Added 1 hour ago
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Software Engineer Internship - Winter 2027
DataVisor
Remote, Canada
- $40,000 to $50,000 CAD / year
- Full-time
- Remote
DataVisor is the world’s leading AI-powered Fraud and Risk Platform that delivers the best overall detection coverage in the industry. With an open SaaS platform that supports easy…
Added 1 hour ago
Senior Quality Engineer (ETL testing)
Scotiabank
Toronto, ON
Google Cloud Platform (GCP): BigQuery, Cloud Composer
Added 1 hour ago
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Senior Developer, Dynamics 365 and Power Platform
Bank of Canada
Toronto, ON
- Full-time
…together to design, develop, and support our regulatory IT platform built on the Power…
Added 1 hour ago
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Technical Delivery Manager
Deloitte
Toronto, ON
- Full-time
3–6 years of experience in product management, technical program management, platform delivery or analytics, with a proven ability to balance competing priorities, make informed trade‑offs,…

Welcome to the Jungle

Senior Forward Deployed Engineer (Gemini Enterprise)

Montreal, QC, Canada

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Job details

Posting language: English
Posted: Nov 4, 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.

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More about this job

Responsibilities

You will design and build end-to-end AI products, including conversational applications and agentic systems, while working embedded with clients. You are responsible for the full delivery lifecycle, from front-end interfaces and backend services to data pipelines and production deployment.

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 computer science or a related field is required, along with strong proficiency in Python, TypeScript, and GCP.

Skills

Gemini Enterprise
Vertex AI
Python
TypeScript
JavaScript
React
RAG
Vector Search
Google Cloud Platform
Agentic Frameworks
Data Engineering
Full-stack Development
API Development
CI/CD
Infrastructure as Code
LLM Evaluation

Visa sponsorship

Not detected in the job text

Keywords

Gemini Enterprise
Vertex AI
Google Cloud Platform
Python
TypeScript
React
RAG
Agentic Systems
Data Engineering
Software Engineering
LLM
BigQuery
Terraform
CI/CD
API
Vector Search
LangGraph
LangChain
Agent Development Kit
Full-stack
Cloud Infrastructure
Machine Learning
Generative AI
Consulting
Data Science
Observability
Version Control
Embeddings
MCP
Prompt Engineering

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