About The Position
Our client is a well-funded, series A, AI startup that builds agents for the factory floor. They develop and distribute a software-first agent layer that plugs into the cameras and machines factories already have and are prototyping robotic arms that extend their agent’s capabilities into the physical world. Their models run and act at the edge so agents can see, decide, and act in real time. Events and metrics flow into a dashboard that provides plant teams immediate visibility. They’re approaching a large (~$140B) and underserved market with a disruptive, asset-light alternative to hardware-heavy robotics and batch analytics. The company has already found traction with manufacturing customers across Quebec, Ontario and the United States, with deployments spanning food and beverage, materials processing, wood processing, plastic extrusion, construction materials and other industrial environments. As a forward deployed engineer, you’ll embed with strategic manufacturing accounts and own the full lifecycle of AI deployments from shop-floor discovery through production handoff. You’ll act as the primary technical contact for customers, code alongside their operations and IT teams, and translate between the realities of the plant floor and the company’s product and engineering roadmap. You’ll scope customer environments, build and integrate production AI systems, troubleshoot live deployments, mature the data flywheel, and hand off stable, documented deployments to the long-term support team. As the company is early in its R&D lifecycle, you will collaborate closely with AI, product, engineering and your project delivery teammates to integrate the learnings from customer deployments to strengthen the platform for the future deployments. You’ll be joining a flat, dynamic environment in the midst of its scale-up phase that’s led by an accomplished ex-Deepmind researcher with specialization in reinforcement learning, deep learning and robotics. The company closed a $13.9M CAD seed round in March of 2025 and are scaling R&D and delivery to meet accelerating demand, with headcount tracking to double by year-end. Please note that this role may involve travel to customer sites across Quebec.
Requirements
- Experience deploying production software into customer environments, ideally as part of an integrated hardware and software system
- Experience with Linux, Docker, Git, cloud environments and deployment workflows
- Familiarity with networking fundamentals like TCP/IP, VLANs and firewalls
- Ability to operate credibly across software, AI and industrial systems, even if deepest expertise skews toward one of those domains
- Command of French and customer-facing maturity to run discovery with operators, discuss architecture with IT/OT leaders, and explain business impact to plant leadership
- Comfort operating in ambiguity, reading the room at a customer site, asking sharp questions and pushing production work forward without waiting for perfect instructions
- Active use of AI-assisted development tools to improve engineering velocity and quality
- Experience collaborating effectively within and across cross-functional delivery teams
- A contagiously curious person with entrenched learning habits
Nice To Haves
- Background in robotics, drones, ROV/AUV systems, remotely piloted vehicles or other field-deployed perception systems
- Experience with industrial vision systems, including camera selection, lighting, optics, lensing or specular reflection mitigation
- Deployed AI or ML models in production on customer infrastructure
- Experience with industrial communication protocols, PLC integration, edge AI deployment, NVIDIA Jetson or industrial vision systems
- Experience with Jetson AGX, BSP flashing, Docker on edge devices or embedded Linux
- Built inference pipelines or real-time systems for constrained environments
- Integrated with ERP systems such as SAP, Oracle or similar enterprise platforms
- Worked in food and beverage, CPG, automotive, packaging, wood processing or other manufacturing verticals
- Experience scaling an AI and/or B2B SaaS venture
Responsibilities
- Embed with strategic manufacturing accounts as the primary technical contact for AI deployments, owning the path from shop-floor scoping through production handoff
- Integrate the platform into customer environments across industrial communication protocols, PLCs, edge inference hardware, and cloud data environments
- Build, configure, deploy and iterate production AI systems that run in real customer infrastructure, including data pipelines, model deployment, system validation and integration testing
- Own the customer-side loop from edge-to-cloud data capture through trained-model deployment, production inference monitoring and feedback with the client
- Diagnose software, networking, integration and deployment issues in active production environments
- Run discovery with operators, controls teams, IT, quality engineers and plant leadership, then translate model performance, accuracy thresholds and ROI into terms different stakeholders can act on
- Produce clear deployment documentation, system configuration records, customer context and handover artifacts that enable the long-term support team to take over confidently
- Feed field signals back into product and engineering, codify repeatable deployment patterns, and contribute to tooling that makes future customer deployments faster and more reliable
Stand Out From the Crowd
Upload your resume and get instant feedback on how well it matches this job.
What This Job Offers
Job Type
Full-time
Career Level
Mid Level
Education Level
No Education Listed
