Forward Deployed Engineer

Location: Montreal

The Role
As a Forward Deployed Engineer​, you embed with our most strategic Quebec​ manufacturing accounts and own the full lifecycle of our AI deployments. You are the primary​ technical contact for the customer, a trusted advisor who codes side-by-side with their operations​ and IT teams, and the two-way translator between shop-floor reality and our product roadmap.

You operate through the FDE lifecycle:

• Phase 1 - Scoping. You land in the customer’s environment and map their systems,​ stakeholders, and pain points. You run discovery directly with operators, controls teams, IT,​ and quality engineers.

• Phase 2 - Build & Integration. You build, deploy, and iterate the AI solution end-to-end:
data pipelines, edge model deployment, OT integration, and data flywheel maturation.

• Phase 3 - Production & Handover. You harden the deployment, document the​ architecture and customer political map, and transfer the account to existing LTS
team. You then rotate to your next account’s Phase 1.
You ship code, not slide decks. You’re measured on outcomes - production AI that actually runs at​ the customer - not billable hours or generic features.
You collaborate closely with the AI Team (model training, MLOps, data exploration) and feed field​ signals back to Product and Engineering so each mandate makes the platform stronger and the
next deployment ships faster.
You report to the Technical Project Manager (Quebec) within the Project Delivery Team. Typical​ allocation: ~50% code, ~30% client (calls, on-site sessions, requirement gathering), ~20% scoping
and project documentation.
Travel:
Up to 25% for on-site commissioning, deep discovery, troubleshooting, and customer​ relationship building.
What You Will Do
Customer Deployment and OT Integration

• Embed with two to four Quebec manufacturing accounts as their primary technical contact​ for AI deployments

• Lead end-to-end deployments of AI vision systems at customer facilities - from​ shop-floor scoping through production handoff

• Integrate​ with the customer’s full operational stack: industrial communication​ protocols (OPC-UA, Modbus TCP, PLCs), edge AI inference (NVIDIA Jetson), customer ERP,​ and customer cloud data environment

• Own the deployment lifecycle: software configuration, system validation, integration​ testing, and production handoff with a formal handover artifact for the LTS team

• Troubleshoot software, networking, and integration issues in live production environments

• Document deployment configurations, system behaviors, and best practices
Technical Customer Engagement

• Serve as the primary technical point of contact during and after deployment

• Train customer operators and engineers on-site and remotely, in French and English

• Participate in occasional pre-sales calls and scoping sessions alongside the sales team

• Translate AI value to non-specialists: model performance, accuracy thresholds, ROI in​ business terms

• Build working relationships with customer technical leads for long-term adoption

Solution Development and Data Flywheel

• Build, deploy, and iterate production AI deployments end-to-end - you own the customerside data flywheel: edge → cloud data capture, trained-model deployment to edge,​ production inference monitoring, and the feedback loop with the client

• Shape the core product roadmap - your field experience directly informs what we build​ next: stability improvements, new platform capabilities, and reusable solutions that scale​ across all customers. Custom work you do at one customer often becomes a standard​ feature for the next.

• Codify deployment patterns and contribute to internal tooling so each mandate makes​ the platform stronger and the next deployment ships faster

• Support data collection and annotation efforts at customer sites when needed

What We Are Looking For ​ Must-Haves

• 6+ years of experience combining production software engineering with industrial​ automation and/or applied AI

• Strong production Python and proven track record shipping systems to customer​ infrastructure - you have deployed real systems that run in front of real users, not just​ prototypes

• Hands-on experience with industrial communication…