Director / VP of Engineering (Computer Vision AI) Location: Greater Toronto Area (Hybrid, Mississauga-based preferred)

ROLE OVERVIEW

Our client operates a high-scale physical operations platform used across large logistics yard environments in North America. The system processes millions of operational events monthly and integrates cameras, sensors, AI pipelines, and enterprise systems (TMS/WMS) into a single operational platform.

The platform functions as mission-critical infrastructure for gate automation, yard operations, and real-time decisioning across distributed sites.

This role owns the end-to-end engineering function and platform direction.

CORE RESPONSIBILITIES

PLATFORM ARCHITECTURE

Own technical direction across the full stack, including:

• Gate automation systems

• Site configuration and multi-tenant workflows

• Integrations with enterprise logistics systems (TMS/WMS)

• Data architecture and event pipelines

• Operator-facing applications and console systems

• AI pipelines for video and sensor stream processing

Make architectural decisions that are expected to scale over multiple years.

ENGINEERING EXECUTION

• Build predictable delivery and planning systems

• Establish clear ownership across teams

• Improve risk management and delivery consistency

• Reduce reliance on hero-based execution

TEAM LEADERSHIP

• Lead and develop engineering managers and senior engineers

• Strengthen organizational structure and accountability

• Hire and scale the next phase of the engineering team

• Maintain technical credibility within the leadership layer

AI-NATIVE ENGINEERING MODEL

• Embed AI tools into the development lifecycle as a core operating model

• Define standards for usage, review, and governance

• Measure impact on delivery speed, quality, and throughput

• Evolve workflows beyond experimental usage into systematic adoption

PRODUCTION RELIABILITY

• Own uptime, observability, incident response, and operational readiness

• Ensure system resilience across distributed, real-world environments

• Establish reliability as a core engineering discipline

SCALING THE PLATFORM

• Support rapid growth in customers, sites, and event volume

• Manage increasing system complexity and integration load

• Account for hybrid cloud and customer-hosted infrastructure environments

BUSINESS ALIGNMENT

• Connect engineering execution to:

  • Product adoption

  • Implementation velocity

  • Operational cost and margin

  • Customer retention and reliability outcomes

WHAT STRONG CANDIDATES DEMONSTRATE

• Clear technical point of view on scaling complex distributed systems

• Ability to identify risks across architecture, integrations, and teams

• Practical experience improving engineering velocity using AI tools in real teams

• Proven ability to remove dependency on key individuals through system design

• Ability to balance speed with predictability in execution

• Strong linkage between engineering decisions and business outcomes

REQUIREMENTS

• 10+ years in software engineering

• 5+ years in engineering leadership roles managing managers or senior engineers

• Progression from developer to engineering management to senior leadership

• Experience building and operating a recurring revenue product platform (B2B SaaS or equivalent)

• Strong cloud architecture experience (AWS, GCP, or equivalent)

• Experience with distributed systems and production-scale services

• Demonstrated use of AI tools in a team-based engineering environment

• Experience operating production systems where uptime and reliability are critical

• Track record of scaling teams beyond hero-based execution models

PREFERRED EXPERIENCE

• GTA-based or willing to work primarily in Mississauga

• Experience in both startup and large-scale engineering environments

• Video streaming or real-time media systems (WebRTC, RTSP, HLS)

• Computer vision systems in production environments

• Hybrid cloud and on-prem infrastructure environments

• Logistics, IoT, security, or industrial workflow systems

NOT A FIT FOR THIS ROLE

• Leaders whose experience is primarily in non-product environments (e.g., consulting, public sector, or purely internal IT)

• Pure people managers without recent technical depth

• Candidates without experience owning production systems end-to-end

• Individuals without hands-on engagement with modern AI engineering workflows

LOGISTICS

• Location: Greater Toronto Area (hybrid, Mississauga-based preferred)

• Reporting to: Founder & CEO, working closely with CTO and operations leadership

• Compensation: Competitive senior engineering package including base, bonus, and equity

• Process:

  • Introductory conversation

  • Technical and architectural working session

  • Team and leadership interviews

  • Executive final conversationon