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Forward Deployed AI Engineer

  • Greater Montreal Metropolitan Area, QC, Canada

$140,000 to $180,000 CAD / year · Full-time

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Job details

Pay
$140,000 to $180,000 CAD / year
Job type
Full-time
Apply by
Posting language
English
Posted

Original job description

Forward Deployed Engineer

A growing international technology organization is hiring four Forward Deployed Engineers to build its Canadian team, primarily in Montreal, with Toronto also considered. Candidates should bring at least three years of relevant experience.

The company and the role

Our client is an established international software company specializing in retail supply-chain planning and optimization, with solutions delivered through a combination of technology and professional services. A dedicated business unit develops operational applications used directly in retail stores across multiple categories, not only grocery.

The business unit grew out of a specialized applied-AI venture that later joined a larger software group. It combines the scale of an established platform with the agility of a focused engineering team. Its solutions support fresh and general-merchandise ordering, in-store production, store execution, inventory, markdowns and expiry-date management. Customer-specific functionality is delivered in days or weeks by engineers working closely with end users.

As a Forward Deployed Engineer, you act as the technical lead and primary engineering contact for retail clients:

  • you engage the whole customer organization, from the executive sponsor to store staff;
  • you gather, challenge and agree on what customers actually need;
  • you write and ship the production code that runs in customer environments;
  • you own the outcomes (KPIs, solution performance, SLAs) until it works;
  • you measure and report the business value delivered, against the customer’s starting point;
  • you spot new opportunities in the account and take them forward with our presales team.

Location and eligibility

  • Based in Montreal (preferred) or Toronto. The Canadian operation is being developed under locally based North American leadership. A dedicated office may be established as the team grows.
  • Full-time position with employment in Canada, either directly or through an employer-of-record arrangement.
  • Legally authorized to work in Canada.
  • Field-embedded: regular travel to customer sites across North America.
  • Four openings now, with at least three years of relevant experience. We set the level on verified experience.

Must-haves

We screen every candidate on these points.

  1. Production code shipped. Notebooks or prototypes alone are not enough.
  1. Hands-on data work: SQL, data modelling, scripting, API integrations. The ideal background is a former data scientist who also does data engineering, with ML or AI deployed to production.
  1. LLMs and agentic workflows as a primary way of working, with the discipline to review what the AI produces.
  1. Customer-facing credibility with both IT teams and executives, and comfortable with travel.
  1. Fluent English, to work with customers across North America.

Strong pluses

  • Bilingual French and English: strongly preferred for the first hires, given collaboration with an international bilingual team.
  • Retail, grocery, supply chain or demand forecasting experience.
  • Cloud platforms (AWS, GCP or Azure) and a modern data stack.
  • Business acumen: turns technical work into measurable financial impact.
  • We want a more gender-balanced team and actively welcome women candidates in every shortlist.

Compensation

Yearly gross package in Canadian dollars, set within the range according to verified seniority and autonomy. We are open so please do not let this be a blocker.

Component

Range (CAD per year)

Base salary

120,000 to 145,000

Variable

20,000 to 30,000

Total

140,000 to 175,000+

Interview process

The process takes about two to three weeks. We give feedback within 48 hours after each step.

  1. Screen: a 30-minute video call with a hiring representative, in English or French.
  1. Technical case: a take-home case on a GitHub repository (about 4 to 8 hours of work), then a 1h30 debrief with one of our FDEs and a software engineer, scheduled in the Montreal morning.
  1. Business case: 45 minutes with a member of the leadership team.
  1. Final meeting: in person with the North American business leader, in Montreal.
  1. Decision and offer.
More about this job

Responsibilities

Lead engineering engagements with retail clients, from gathering and validating requirements to building and deploying production code in customer environments. Own solution performance and business outcomes, report measurable value, and identify opportunities in client accounts.

Requirements

Candidates need at least three years of relevant experience, a record of shipping production code, and hands-on experience with SQL, data modeling, scripting, API integrations, and production AI or machine learning. They must be credible with both technical teams and executives, comfortable with regular travel, and fluent in English; French-English bilingualism and retail or supply-chain experience are strong advantages.

Skills

  • SQL
  • Data Modeling
  • Scripting
  • API Integration
  • Data Engineering
  • Machine Learning
  • Artificial Intelligence
  • Large Language Models
  • Agentic Workflows
  • Customer Engagement
  • Cloud Platforms
  • Business Acumen
  • Retail Supply Chain
  • Demand Forecasting
  • English Communication

Visa sponsorship

Not detected in the job text

Categories

  • Technology
  • Software
  • Engineering
  • Data & Analytics
  • Retail

Keywords

  • Forward Deployed Engineering
  • Production Code
  • SQL
  • Data Modeling
  • Scripting
  • API Integration
  • Data Engineering
  • Data Science
  • Machine Learning
  • Artificial Intelligence
  • Large Language Models
  • Agentic Workflows
  • Retail
  • Supply Chain Planning
  • Demand Forecasting
  • Inventory Management
  • Store Execution
  • Markdowns
  • Expiry-Date Management
  • AWS
  • Google Cloud Platform
  • Microsoft Azure
  • Modern Data Stack
  • Customer Engagement
  • Service-Level Agreements
  • Key Performance Indicators
  • Business Value Measurement
  • Presales

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