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Senior Software Engineering Manager

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Onsite

Senior Software Engineering Manager

Motorola Solutions

Senior Software Engineering Manager

Skills

TableauReactTesting & QAMachine LearningAIAWSLinuxWorkdayProcess ImprovementJavascript

2 months ago

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Important information


Contract type:

Permanent

Location:

Canada

Work mode:

Onsite

Published on:

17 August 2026

What they need


  • Our Engineering department is seeking a technical leader to advance new machine learning solutions for our product line
  • Engineering Management: Lead talented engineers to accomplish strategic goals aligned with the services, features, and functionality we deliver for our core products
  • Release Management: Drive the planning, execution, and communication of appliance releases
  • Process Improvements: Continuously identify and implement improvements to our release processes, tools, and methodologies, including customer-facing interfaces and processes
  • Technical Direction: As a technical manager who has had hands-on development experience in the past, leverage deep technical expertise to guide architecture and strategic direction of our appliance software and internal tooling
  • Cross-Functional Coordination: Work collaboratively with engineering, product, customer success, sales and support teams to align release schedules and priorities
  • Fielded Device Health Monitoring: Proactively monitor the health and performance of Envysion connected devices deployed to customers, identifying trends and addressing any issues promptly
  • Bachelors degree with 8+ years of software engineering experience
  • AND 4+ years of leading/people management experience

Benefits

  • Flexible work models
  • Paid time off
  • Paid parental and family leave
  • Health care benefits
  • Global wellness resources
  • Employee assistance programs
  • Rotation programs
  • Mentor relationships
  • Learning and development opportunities
  • Retirement benefits
  • Employee bonuses
  • Stock grants & employee stock purchase plans- AI/Inference - Working understanding of AI inference engines (e.g YOLO, OpenCV)
  • Attention to Detail: Meticulous attention to detail and a commitment to delivering high-quality, stable releases
  • Leadership: Leading software and QA engineers successfully accomplishing established goals
  • Problem-Solving: Strong analytical and problem-solving skills with a focus on root cause analysis and prevention measures
  • Experience: Proven experience as a Team Lead, Engineering Manager, Release Manager, or similar role working on Cloud managed Video solutions
  • Collaboration: A team player who thrives in a collaborative environment and can build strong relationships across departments
  • Communication: Excellent verbal and written communication skills, with the ability to articulate complex technical information clearly to diverse audiences
  • Distributed Team Management: Proven experience managing cross-border hybrid/remote engineering teams, balancing asynchronous workflows with real-time collaboration
  • Technical Skills: 8+ years prior hands-on experience developing with technologies such as Relational Databases, JavaScript, C++, and React. Understanding of build systems, CI/CD pipelines, and configuration management. Experience with cloud technologies (particularly AWS) and Restful APIs is helpful. Familiarity with video streaming such as HLS and related technologies
  • AI/Automation: Experience leveraging AI tools and a strong understanding of how to identify and implement AI-driven opportunities within the software development lifecycle and workflows
  • Experience with surveillance video camera hardware
  • Embedded Linux & System-Level Knowledge: Experience with Linux OS customization, kernel updates, system, disk storage management and filesystem resiliency
  • Familiarity with physical access control systems or security products
  • Use of Business Intelligence tools such as Tableau or Quicksight
  • Edge Resource Management: Understanding hardware constraint budgets when running simultaneous high-definition video recording, streaming, and edge computer vision/AI inference engines
  • Hardware/Lab Operations: Experience managing hardware test labs, physical test rig automation, test bench setup, and camera/sensor interoperability testing (ONVIF standards, RTSP streams, IP camera compatibility)

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