Job Description

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 and/or edge AI deployment - at​ least 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 edge​ hardware

• Solid networking fundamentals (TCP/IP, VLANs, firewalls) as they apply to industrial​ deployments

• 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 a​ technical design document in English without losing precision

• High agency, bias for action - you operate well in ambiguity and ship production code on​ customer 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 the​ systems / 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 skews​ one direction. You know enough about ML to have a real conversation about model performance​ and 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 (Greater​ Montreal, Quebec City, Sherbrooke, Trois-Rivières, or elsewhere). Proximity to​ manufacturing customers required for periodic on-site work.

• Up to 25% travel for on-site commissioning, deep discovery, troubleshooting, and​ customer 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 expect​ you to use AI in your daily workflow.

Why ​Us

• 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 growth​ is 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