VP Engineering w/ Award Winning AI Startup || Toronto


Our client develops and licenses its artificial intelligence construction analytics platform. The SaaS 3D computer vision platform enables developers, project managers, and general contractors to optimize labor, equipment, and materials. The platform uses live video streams from secure IP cameras to uncover inefficiencies on construction sites. The software is powered by a proprietary machine vision neural network that can accurately recognize 100+ types of construction equipment and activities.

They launched their first customer agreement in late 2017 and their sales pipeline is now growing faster than is manageable (they have grown 1100% in 10 months). Their priorities is to build a world class product and engineering team capable of scaling our AI platforms to ingest thousands of video feeds and provide real-time actionable insights to save millions of dollars for the construction industry. They have secured $8M in Series A funding (less than 15 months after raising our seed), for a total of $11.7M raised to date.


  • You will be the technical leader in their growing company. 
  • They’ve successfully raised funding, won some of the best brands in our target market, and now are ready to build the best video analytics pipeline and application platform using world class R&D, Engineering, DevOps, and QA methodologies.
  • You will be responsible for defining, implementing and scaling their R&D, Engineering, DevOps, and QA-AI data analytics organizations. 
  • Reporting to the Chief Executive Officer, you'll lead the growth and expansion of their entire technical function and become a core member of their Senior Leadership Team.
  • 8+ years Technical leadership experience
  • 10+ years software engineering experience
  • Bachelor's level degree in computer science, engineering, math or related field; or relevant work experience
  • Very strong computer science fundamentals (data structures and algorithms)
  • Strong understanding of statistics and mathematics
  • Strong system design experience
  • Knowledge of Software Engineerin, DevOps, Data Science; Computer Vision & Machine Learning, QA
  • Experience with large scale systems, parallel computing, distributed storage