Join Haldorix, a startup studio turning real-world operational challenges into scalable business opportunities through technology. We identify recurring problems in industries such as manufacturing, retail, and logistics, and transform them into ventures with measurable impact. We’re looking for a Tech Architect to lead the design and validation of a real-time industrial vision system for monitoring productivity on textile production lines. This is an intensive initiative aimed at delivering a fully functional, field-ready solution, ideal for an engineer who thrives on fast execution and tangible results.

- Architect & Design: Define the overall system architecture and ensure cohesion across components and technologies. - Field Deployment: Oversee on-site installation and calibration of AprilTags, cameras, and network components. - Quality Assurance: Coordinate QA activities and conduct end-to-end acceptance testing in production environments. - Monitoring Setup: Configure and validate observability dashboards using Grafana and business-specific KPIs. - Documentation: Produce comprehensive technical and operational documentation to support deployment and scalability. - Cross-Functional Collaboration: Act as the bridge between technical and business stakeholders, ensuring alignment between field needs and system capabilities. - Continuous Improvement: Identify optimization opportunities and propose architecture adjustments based on real-world performance feedback.

You’ll join a multidisciplinary task force of engineers, computer-vision experts, and product innovators working under Haldorix’s venture-building model. Collaboration is tight-knit and execution-driven. Every decision directly impacts the success of the project. You’ll work alongside technical leads, and collaborate with on-site operators to validate system performance in real conditions.

Required - 3+ years of experience in system architecture - Strong understanding of resilient, distributed systems design - Hands-on knowledge of Kubernetes, Prometheus, and Grafana - Familiarity with Computer Vision systems and on-field hardware calibration - Solid foundation in QA methodologies and field validation processes - Excellent communication and documentation skills in English and/or French Nice to Have - Prior experience in industrial automation or IoT environments - Familiarity with AprilTags, camera calibration, or real-time data pipelines - Exposure to Python, FastAPI, or edge-AI deployment workflows - Previous work in a startup environment

- Immediate impact through a high-intensity, real-world project - Opportunity to shape a new industrial AI venture from its early stages - Work directly with cross-disciplinary experts at the frontier of AI and operations - A mission-driven environment that values autonomy, clarity, and purpose