Focus on building, deploying, and supporting AI software systems that power customer-facing deployments
Work closely with Deployment Engineers, Systems Design, ML, and Infrastructure teams
Develop and maintain deployment-ready software stacks
Implement custom modules or services required for specific customer applications
Ensure systems meet performance, reliability, and operational requirements across edge and cloud environments
Requirements
Degree in Computer Science, Software Engineering, or equivalent industry experience
Strong experience supporting production software deployments and feature development
Experience with cloud and/or edge infrastructure, including Linux-based systems
Solid backend development skills in Python, C/C++, or equivalent
Experience with implementing image processing and computer vision applications with tools such as OpenCV
Familiarity with DevOps practices: CI/CD, containerization, configuration management
Ability to debug issues across application code, infrastructure, and runtime environments
Strong collaboration skills with hardware, deployment, and customer-facing teams
Willingness to travel to customer deployments in Canada and the United States as needed
Full-stack or frontend web development experience, particularly with TypeScript and React, to support user interfaces and operational tools for deployed AI applications
Prior experience working with fault-tolerant edge AI systems in production environments
Experience with edge fleet management, including device provisioning, lifecycle management, health monitoring, and remote updates
Familiarity with tracking edge device activities, telemetry, logs, and operational metrics across distributed deployments
Experience deploying and maintaining software on distributed, intermittently connected, or resource-constrained edge devices
Experience with real-time systems or low-latency applications
Expertise in inference optimization (model serving, performance tuning, hardware acceleration)
Familiarity with Docker, Kubernetes, or lightweight orchestration at the edge
Exposure to monitoring and observability tools (Prometheus, Grafana, ELK, etc.)
Experience working in industrial, robotics, or manufacturing environments
Prior work in startup or fast-paced customer-facing engineering teams
Tech Stack
Cloud
Docker
Grafana
Kubernetes
Linux
Prometheus
Python
React
TypeScript
Benefits
Build software powered by cutting-edge AI that runs in real factories, not just dashboards
Own deployment-critical systems with direct customer impact
Work across edge, cloud, and real-time AI systems
Collaborate with world-class engineers and AI researchers in a fast-growing startup