Forward Deployed Engineer

The Role
As a Forward Deployed Engineer you embed with our most strategic Quebecmanufacturing accounts and own the full lifecycle of our AI deployments. You are the primarytechnical contact for the customer a trusted advisor who codes side-by-side with their operationsand 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 customers environment and map their systemsstakeholders and pain points. You run discovery directly with operators controls teams ITand 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 thearchitecture and customer political map and transfer the account to existing LTS
team. You then rotate to your next accounts Phase 1.
You ship code not slide decks. Youre measured on outcomes - production AI that actually runs atthe customer - not billable hours or generic features.
You collaborate closely with the AI Team (model training MLOps data exploration) and feed fieldsignals 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. Typicalallocation: 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 customerrelationship building.
What You Will Do
Customer Deployment and OT Integration
Embed with two to four Quebec manufacturing accounts as their primary technical contactfor AI deployments
Lead end-to-end deployments of AI vision systems at customer facilities - fromshop-floor scoping through production handoff
Integratewith the customers full operational stack: industrial communicationprotocols (OPC-UA Modbus TCP PLCs) edge AI inference (NVIDIA Jetson) customer ERPand customer cloud data environment
Own the deployment lifecycle: software configuration system validation integrationtesting 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 inbusiness 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 edgeproduction inference monitoring and the feedback loop with the client
Shape the core product roadmap - your field experience directly informs what we buildnext: stability improvements new platform capabilities and reusable solutions that scaleacross all customers. Custom work you do at one customer often becomes a standardfeature for the next.
Codify deployment patterns and contribute to internal tooling so each mandate makesthe platform stronger and the next deployment ships faster
Support data collection and annotation efforts at customer sites when needed



What We Are Looking ForMust-Haves
6 years of experience combining production software engineering with industrialautomation and/or applied AI
Strong production Python and proven track record shipping systems to customerinfrastructure - you have deployed real systems that run in front of real users not justprototypes
Hands-on experience with industrial communication and/or edge AI deployment - atleast one of: OPC-UA / Modbus / PLC integration Jetson or equivalent edge platformsGenICam / industrial vision systems
Cloud experience - comfortable deploying and operating services in cloud environments(AWS / Azure / GCP)
Strong software fundamentals: Python Linux Docker Git comfort deploying to edgehardware
Solid networking fundamentals (TCP/IP VLANs firewalls) as they apply to industrialdeployments
Customer-facing seniority - you can hold the line in a discovery workshop with operatorsan architecture review with the IT/OT director and an executive briefing with the plant
manager in the same week
Bilingual French and English - you can run a discovery workshop in French and write atechnical design document in English without losing precision
High agency bias for action - you operate well in ambiguity and ship production code oncustomer infrastructure
Nice-to-Haves
Direct experience deploying AI/ML models in production on customer infrastructure
Industrial automation experience at large (PLC integration controls manufacturing
systems)
Industrial vision: GenICam / GigE cameras (Basler Lucid Cognex Keyence) OpenCVoptical intuition (lens selection lighting specular reflection mitigation)
Specific ERP integration: SAP Oracle or similar
Jetson AGX (flash BSP Docker edge embedded Linux)
AI/ML inference pipelines and real-time systems
Background in mobile robotics drones ROV/AUV or remotely piloted vehicles - shares thesystems / embedded / perception / field-integration DNA
Background in food and beverage CPG automotive packaging or wood processing
Experience in a startup or high-growth environment where you have worn multiple hats


Who Thrives Here
You are comfortable operating in ambiguity. You can walk into a customer facility read the roomunderstand what matters to their operation and start solving problems without waiting to be told
exactly what to do. You have a high bar for what working actually are technically credible across software AI and industrial systems even if your depth skewsone direction. You know enough about ML to have a real conversation about model performanceand drift and enough about OT to own integration with PLCs and ERPs. You learn fast and ask good
questions. You care about the customer outcome not just task completion.
Logistics
Based in Quebec 100% remote - you work from home anywhere in Quebec (GreaterMontreal Quebec City Sherbrooke Trois-Rivières or elsewhere). Proximity tomanufacturing customers required for periodic on-site work.
Up to 25% travel for on-site commissioning deep discovery troubleshooting andcustomer relationship building
Bilingual French and English required
Mid-Senior individual contributor role reporting to the Technical Project Manager(Quebec) within the Project Delivery Team


Compensation
Competitive compensation and benefits. Cursor / Claude Code subscription included - we expectyou to use AI in your daily workflow.


WhyUs
Work on AI systems that have direct measurable impact on real manufacturing operations
Join a technically deep team at a stage where your contributions are visible and your growthis real
Own meaningful customer relationships and deployments end-to-end
Each mandate produces a documented handover that survives any individual departure -your work compounds across customers and across the platform

Required Experience:

IC

Employment Type : Full Time
Experience: years
Vacancy: 1