Forward Deployed Engineer

hireVouch

3d•Remote

About The Position

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.

Requirements

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

Responsibilities

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
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
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