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About the Role

This role owns the end-to-end engineering function and platform direction for a high-scale physical operations platform used across large logistics yard environments. The platform integrates cameras, sensors, AI pipelines, and enterprise systems into a single operational system that functions as mission-critical infrastructure.

Responsibilities

• 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, and AI pipelines for video and sensor stream processing.
• Make architectural decisions that are expected to scale over multiple years.
• Build predictable delivery and planning systems.
• Establish clear ownership across teams.
• Improve risk management and delivery consistency.
• Reduce reliance on hero-based execution.
• 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.
• Embed AI tools into the development lifecycle as a core operating model.
• Define standards for usage, review, and governance of AI tools.
• Measure impact of AI tools on delivery speed, quality, and throughput.
• Evolve AI workflows beyond experimental usage into systematic adoption.
• Own uptime, observability, incident response, and operational readiness.
• Ensure system resilience across distributed, real-world environments.
• Establish reliability as a core engineering discipline.
• 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.
• Connect engineering execution to product adoption, implementation velocity, operational cost and margin, and customer retention and reliability 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.

Skills

• Scaling complex distributed systems
• Identifying risks across architecture, integrations, and teams
• Improving engineering velocity using AI tools
• Removing dependency on key individuals through system design
• Balancing speed with predictability in execution
• Linking engineering decisions to business outcomes
• Cloud architecture (AWS, GCP, or equivalent)
• Distributed systems
• Production-scale services
• AI tools in a team-based engineering environment
• Production systems operation
• Uptime and reliability
• 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

Location

• Greater Toronto Area
• Mississauga

Work Type

• Hybrid

Experience Level

• 10+ years in software engineering
• 5+ years in engineering leadership roles

Salary/Compensations

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

About the Company

• 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.