Internship Forward Deployed Software Engineer Jobs in Quebec

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 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 thearchitecture 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 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 customer's full operational stack: industrial communicationprotocols (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, 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 edge,production 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 platforms,GenICam / 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 operators,an 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), OpenCV,optical 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 room,understand 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 means.You 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-Rivieres, 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