Sr. Software Engineer - AILocation: Remote – Toronto, ON
A stealth-mode innovator in the AI-driven manufacturing sector is seeking a highly skilled Sr. AI Software Engineer to build and deploy reliable, real-time solutions on edge devices within industrial environments. This is a remote position based in the Greater Toronto Area, offering the opportunity to work on groundbreaking tech shaping the future of factory automation.
This role is for a hands-on developer with a passion for optimizing industrial operations through vision AI, robust system architecture, and scalable data infrastructure. You’ll collaborate with world-class engineers and AI scientists to translate cutting-edge research into real-world impact.
Key ResponsibilitiesDesign and implement robust on-premise infrastructure to power real-time AI vision systems on Linux-based edge devices.Develop and maintain production-grade applications handling AI inference, image processing, and system health monitoring.Engineer OTA (Over-The-Air) deployment systems and build fleet-wide software orchestration capabilities for distributed device networks.Integrate with industrial hardware systems, including PLCs, and legacy manufacturing execution systems (MES).Implement error recovery mechanisms, real-time monitoring, alerting, and reliability safeguards to ensure system uptime in mission-critical environments.Contribute to the development of a centralized data platform that supports industrial analytics, facility optimization, and predictive insights.Work with cross-functional teams to integrate AI vision workflows into safety, inspection, and quality control operations.Optimize software performance for constrained, latency-sensitive edge environments.Ensure secure, scalable communication across IoT devices and industrial protocols.
QualificationsMust-Have:Strong software engineering foundation with 3–5 years of experience developing production-ready systems, especially in manufacturing or industrial settings.Proficient in Python, Linux environments, and system-level development.Hands-on experience with containerization (e.g., Docker) and modern DevOps practices.Familiarity with deploying AI/ML inference pipelines and computer vision tools.Knowledge of system reliability design (monitoring, graceful degradation, recovery strategies).Exposure to hybrid cloud-edge deployments across platforms like AWS, GCP, or Azure.Experience with device management, IoT communication protocols (MQTT, REST), and fleet-wide orchestration.Preferred:Experience with web development tools (TypeScript, React) for dashboards and operator interfaces.Familiarity with edge AI platforms like NVIDIA Jetson.Understanding of industrial networking and automation protocols (Modbus, OPC-UA, Ethernet/IP).Prior work on OTA update systems in resource-constrained environments.Strong debugging skills and problem-solving in uptime-critical environments.Bonus Points:Knowledge of time-series databases (InfluxDB, Prometheus, Grafana).Experience with manufacturing data platforms, MES, or QMS.Background in vision systems, OpenCV, TensorFlow, or PyTorch.Sector experience in food & beverage, automotive, or consumer goods manufacturing is a plus.
What’s In It For YouShape the future of AI-driven factory automation with a high-growth startup.Work alongside globally recognized AI experts and engineers.Make tangible impact in production environments - not just prototypes or lab experiments.Full remote flexibility with occasional travel to industrial sites or conferences (if interested).Competitive compensation package aligned with fast-paced startup environments.
If you're a platform-oriented software engineer who thrives on performance, uptime, and deploying real-time intelligence in the physical world, this is your next career-defining opportunity.
About Blue Signal:Blue Signal is an award-winning, executive search firm specializing in various specialties. Our recruiters have a proven track record of placing top-tier talent across industry verticals, with deep expertise in numerous professional services. Learn more at bit.ly/46Gs4yS
Sr. Software Engineer - AILocation: Remote – Toronto, ON
A stealth-mode innovator in the AI-driven manufacturing sector is seeking a highly skilled Sr. AI Software Engineer to build and deploy reliable, real-time solutions on edge devices within industrial environments. This is a remote position based in the Greater Toronto Area, offering the opportunity to work on groundbreaking tech shaping the future of factory automation.
This role is for a hands-on developer with a passion for optimizing industrial operations through vision AI, robust system architecture, and scalable data infrastructure. You’ll collaborate with world-class engineers and AI scientists to translate cutting-edge research into real-world impact.
Key ResponsibilitiesDesign and implement robust on-premise infrastructure to power real-time AI vision systems on Linux-based edge devices.Develop and maintain production-grade applications handling AI inference, image processing, and system health monitoring.Engineer OTA (Over-The-Air) deployment systems and build fleet-wide software orchestration capabilities for distributed device networks.Integrate with industrial hardware systems, including PLCs, and legacy manufacturing execution systems (MES).Implement error recovery mechanisms, real-time monitoring, alerting, and reliability safeguards to ensure system uptime in mission-critical environments.Contribute to the development of a centralized data platform that supports industrial analytics, facility optimization, and predictive insights.Work with cross-functional teams to integrate AI vision workflows into safety, inspection, and quality control operations.Optimize software performance for constrained, latency-sensitive edge environments.Ensure secure, scalable communication across IoT devices and industrial protocols.
QualificationsMust-Have:Strong software engineering foundation with 3–5 years of experience developing production-ready systems, especially in manufacturing or industrial settings.Proficient in Python, Linux environments, and system-level development.Hands-on experience with containerization (e.g., Docker) and modern DevOps practices.Familiarity with deploying AI/ML inference pipelines and computer vision tools.Knowledge of system reliability design (monitoring, graceful degradation, recovery strategies).Exposure to hybrid cloud-edge deployments across platforms like AWS, GCP, or Azure.Experience with device management, IoT communication protocols (MQTT, REST), and fleet-wide orchestration.Preferred:Experience with web development tools (TypeScript, React) for dashboards and operator interfaces.Familiarity with edge AI platforms like NVIDIA Jetson.Understanding of industrial networking and automation protocols (Modbus, OPC-UA, Ethernet/IP).Prior work on OTA update systems in resource-constrained environments.Strong debugging skills and problem-solving in uptime-critical environments.Bonus Points:Knowledge of time-series databases (InfluxDB, Prometheus, Grafana).Experience with manufacturing data platforms, MES, or QMS.Background in vision systems, OpenCV, TensorFlow, or PyTorch.Sector experience in food & beverage, automotive, or consumer goods manufacturing is a plus.
What’s In It For YouShape the future of AI-driven factory automation with a high-growth startup.Work alongside globally recognized AI experts and engineers.Make tangible impact in production environments - not just prototypes or lab experiments.Full remote flexibility with occasional travel to industrial sites or conferences (if interested).Competitive compensation package aligned with fast-paced startup environments.
If you're a platform-oriented software engineer who thrives on performance, uptime, and deploying real-time intelligence in the physical world, this is your next career-defining opportunity.
About Blue Signal:Blue Signal is an award-winning, executive search firm specializing in various specialties. Our recruiters have a proven track record of placing top-tier talent across industry verticals, with deep expertise in numerous professional services. Learn more at bit.ly/46Gs4yS
Edge Performance Engineer - AILocation: Remote – Canada or Greater Toronto Area
A leading innovator in edge-based AI solutions is seeking a highly skilled Edge Performance Engineer to join their growing team. This cutting-edge role is at the intersection of hardware and AI, focusing on the optimization of GPU-accelerated vision pipelines running at the edge. This is a rare opportunity to influence the design and deployment of real-time computer vision systems across industrial and automation environments, with the support of a well-funded and visionary organization.
In this position, you'll take full ownership of the edge system performance lifecycle, from profiling and model optimization to system integration and observability. You’ll work cross-functionally with machine learning, DevOps, and cloud engineering teams to ensure consistent, high-throughput inference at the edge. The ideal candidate thrives in resource-constrained environments and enjoys solving complex system-level challenges involving hardware acceleration, system bottlenecks, and runtime tuning.
Key ResponsibilitiesOptimize performance of GPU-accelerated computer vision pipelines on edge hardware (e.g., NVIDIA Jetson, x86/ARM systems).Improve throughput and reduce latency through advanced model optimization techniques (e.g., quantization, TensorRT, ONNX Runtime).Profile and resolve system-level constraints across CPU, GPU, memory, storage, and network layers.Collaborate with machine learning teams to deploy robust models that meet real-world resource constraints.Integrate edge systems with observability and orchestration frameworks to ensure maintainability and scale.Develop dashboards and tools to monitor edge performance KPIs like frame rate, latency, uptime, and resource usage.Participate in root cause investigations for performance-related incidents on production systems.Provide technical input on system design and hardware selection for new edge deployments.
What You'll Bring5+ years of experience in software engineering with a focus on high-performance or real-time systems.Strong background in GPU-accelerated development using CUDA, TensorRT, cuDNN, or equivalent vendor tools.Proficiency in Python and at least one systems language such as C++ or Rust.Proven experience in deploying and optimizing deep learning inference pipelines in production environments.Advanced Linux skills and comfort using observability tools (e.g., perf, strace, eBPF).Experience working with Docker and CI/CD workflows targeting edge devices.Deep debugging capabilities across application, system, and hardware levels.Preferred QualificationsBackground in edge AI, robotics, or industrial automation applications.Familiarity with video processing frameworks (e.g., GStreamer).Understanding of edge-specific challenges such as thermal throttling, intermittent connectivity, and limited bandwidth.Exposure to Kubernetes or other edge orchestration frameworks.
Why JoinWork at the forefront of AI and computer vision innovation.Solve tangible, high-impact problems in real-world deployments.Join a mission-driven team with strong technical leadership and cross-functional collaboration.Enjoy a flexible, remote-first work culture with top-tier talent across Canada and beyond.
About Blue Signal: Blue Signal is an award-winning, executive search firm specializing in various specialties. Our recruiters have a proven track record of placing top-tier talent across industry verticals, with deep expertise in numerous professional services. Learn more at bit.ly/46Gs4yS
Edge Performance Engineer - AILocation: Remote – Canada or Greater Toronto Area
A leading innovator in edge-based AI solutions is seeking a highly skilled Edge Performance Engineer to join their growing team. This cutting-edge role is at the intersection of hardware and AI, focusing on the optimization of GPU-accelerated vision pipelines running at the edge. This is a rare opportunity to influence the design and deployment of real-time computer vision systems across industrial and automation environments, with the support of a well-funded and visionary organization.
In this position, you'll take full ownership of the edge system performance lifecycle, from profiling and model optimization to system integration and observability. You’ll work cross-functionally with machine learning, DevOps, and cloud engineering teams to ensure consistent, high-throughput inference at the edge. The ideal candidate thrives in resource-constrained environments and enjoys solving complex system-level challenges involving hardware acceleration, system bottlenecks, and runtime tuning.
Key ResponsibilitiesOptimize performance of GPU-accelerated computer vision pipelines on edge hardware (e.g., NVIDIA Jetson, x86/ARM systems).Improve throughput and reduce latency through advanced model optimization techniques (e.g., quantization, TensorRT, ONNX Runtime).Profile and resolve system-level constraints across CPU, GPU, memory, storage, and network layers.Collaborate with machine learning teams to deploy robust models that meet real-world resource constraints.Integrate edge systems with observability and orchestration frameworks to ensure maintainability and scale.Develop dashboards and tools to monitor edge performance KPIs like frame rate, latency, uptime, and resource usage.Participate in root cause investigations for performance-related incidents on production systems.Provide technical input on system design and hardware selection for new edge deployments.
What You'll Bring5+ years of experience in software engineering with a focus on high-performance or real-time systems.Strong background in GPU-accelerated development using CUDA, TensorRT, cuDNN, or equivalent vendor tools.Proficiency in Python and at least one systems language such as C++ or Rust.Proven experience in deploying and optimizing deep learning inference pipelines in production environments.Advanced Linux skills and comfort using observability tools (e.g., perf, strace, eBPF).Experience working with Docker and CI/CD workflows targeting edge devices.Deep debugging capabilities across application, system, and hardware levels.Preferred QualificationsBackground in edge AI, robotics, or industrial automation applications.Familiarity with video processing frameworks (e.g., GStreamer).Understanding of edge-specific challenges such as thermal throttling, intermittent connectivity, and limited bandwidth.Exposure to Kubernetes or other edge orchestration frameworks.
Why JoinWork at the forefront of AI and computer vision innovation.Solve tangible, high-impact problems in real-world deployments.Join a mission-driven team with strong technical leadership and cross-functional collaboration.Enjoy a flexible, remote-first work culture with top-tier talent across Canada and beyond.
About Blue Signal: Blue Signal is an award-winning, executive search firm specializing in various specialties. Our recruiters have a proven track record of placing top-tier talent across industry verticals, with deep expertise in numerous professional services. Learn more at bit.ly/46Gs4yS
DevOps EngineerLocation: Remote (Canada-wide) with preference for applicants in the Greater Toronto Area
About the CompanyOur client is a confidential, venture-backed pioneer at the intersection of AI, computer vision, and industrial automation. Their edge-focused platform is already improving safety and efficiency on factory floors across North America, and they are scaling fast.
Why This Role RocksBuild a green-field infrastructure layer that bridges cloud and edge for thousands of devices.Work in a fully remote, senior-only engineering culture that values autonomy and rapid iteration.See your work ship to real machines—impact measured in uptime, not vanity metrics.Competitive salary, meaningful early-stage equity, and first-class benefits.
Compensation & BenefitsMarket-competitive base pay plus meaningful equity.Flexible hours, 100 percent remote setup, and an annual home-office stipend.Comprehensive health, dental, vision, and mental-health coverage.Generous PTO, quarterly recharge Fridays, and a professional development budget.
Key ResponsibilitiesEngineer and automate the cloud-plus-edge backbone that keeps thousands of Linux-based devices online, healthy, and secure.Manage Kubernetes clusters that power GPU-accelerated computer-vision workloads in both public cloud and on-prem customer sites.Design and own zero-touch deployment pipelines that support blue/green, canary, and instant rollback strategies for over-the-air updates.Codify infrastructure with Terraform, Helm, and similar tools so every environment spins up the same way every time.Embed scalable observability with Prometheus, Grafana, and OpenTelemetry to surface fleet health and performance insights in real time.Partner with SRE and software teams to deliver resilient, easy-to-deploy microservices and APIs.Lead post-incident reviews, driving systemic fixes that strengthen reliability release after release.Champion security best practices around identity, secrets management, and network segmentation across cloud and edge footprints.
What You Bring5+ years in DevOps, Platform, or Site Reliability Engineering.Hands-on experience running Kubernetes in production and troubleshooting containerized workloads.Proficiency with Infrastructure-as-Code (Terraform, Helm, Ansible, or equivalents).Strong scripting or development skills in Python, Go, or a comparable language.Deep Linux knowledge plus solid fundamentals in networking and performance tuning.Practical experience with CI/CD pipelines (GitHub Actions, GitLab CI, Jenkins, etc.).Exposure to distributed or hybrid cloud/edge systems; GPU scheduling or industrial IoT is a plus.Clear, collaborative communication style and a bias for owning problems end-to-end.
About Blue Signal: Blue Signal is an award-winning, executive search firm specializing in various specialties. Our recruiters have a proven track record of placing top-tier talent across industry verticals, with deep expertise in numerous professional services. Learn more at bit.ly/46Gs4yS
DevOps EngineerLocation: Remote (Canada-wide) with preference for applicants in the Greater Toronto Area
About the CompanyOur client is a confidential, venture-backed pioneer at the intersection of AI, computer vision, and industrial automation. Their edge-focused platform is already improving safety and efficiency on factory floors across North America, and they are scaling fast.
Why This Role RocksBuild a green-field infrastructure layer that bridges cloud and edge for thousands of devices.Work in a fully remote, senior-only engineering culture that values autonomy and rapid iteration.See your work ship to real machines—impact measured in uptime, not vanity metrics.Competitive salary, meaningful early-stage equity, and first-class benefits.
Compensation & BenefitsMarket-competitive base pay plus meaningful equity.Flexible hours, 100 percent remote setup, and an annual home-office stipend.Comprehensive health, dental, vision, and mental-health coverage.Generous PTO, quarterly recharge Fridays, and a professional development budget.
Key ResponsibilitiesEngineer and automate the cloud-plus-edge backbone that keeps thousands of Linux-based devices online, healthy, and secure.Manage Kubernetes clusters that power GPU-accelerated computer-vision workloads in both public cloud and on-prem customer sites.Design and own zero-touch deployment pipelines that support blue/green, canary, and instant rollback strategies for over-the-air updates.Codify infrastructure with Terraform, Helm, and similar tools so every environment spins up the same way every time.Embed scalable observability with Prometheus, Grafana, and OpenTelemetry to surface fleet health and performance insights in real time.Partner with SRE and software teams to deliver resilient, easy-to-deploy microservices and APIs.Lead post-incident reviews, driving systemic fixes that strengthen reliability release after release.Champion security best practices around identity, secrets management, and network segmentation across cloud and edge footprints.
What You Bring5+ years in DevOps, Platform, or Site Reliability Engineering.Hands-on experience running Kubernetes in production and troubleshooting containerized workloads.Proficiency with Infrastructure-as-Code (Terraform, Helm, Ansible, or equivalents).Strong scripting or development skills in Python, Go, or a comparable language.Deep Linux knowledge plus solid fundamentals in networking and performance tuning.Practical experience with CI/CD pipelines (GitHub Actions, GitLab CI, Jenkins, etc.).Exposure to distributed or hybrid cloud/edge systems; GPU scheduling or industrial IoT is a plus.Clear, collaborative communication style and a bias for owning problems end-to-end.
About Blue Signal: Blue Signal is an award-winning, executive search firm specializing in various specialties. Our recruiters have a proven track record of placing top-tier talent across industry verticals, with deep expertise in numerous professional services. Learn more at bit.ly/46Gs4yS
DevOps EngineerLocation: Remote (Canada-wide) with preference for applicants in the Greater Toronto Area
About the CompanyOur client is a confidential, venture-backed pioneer at the intersection of AI, computer vision, and industrial automation. Their edge-focused platform is already improving safety and efficiency on factory floors across North America, and they are scaling fast.
Why This Role RocksBuild a green-field infrastructure layer that bridges cloud and edge for thousands of devices.Work in a fully remote, senior-only engineering culture that values autonomy and rapid iteration.See your work ship to real machines—impact measured in uptime, not vanity metrics.Competitive salary, meaningful early-stage equity, and first-class benefits.
Compensation & BenefitsMarket-competitive base pay plus meaningful equity.Flexible hours, 100 percent remote setup, and an annual home-office stipend.Comprehensive health, dental, vision, and mental-health coverage.Generous PTO, quarterly recharge Fridays, and a professional development budget.
Key ResponsibilitiesEngineer and automate the cloud-plus-edge backbone that keeps thousands of Linux-based devices online, healthy, and secure.Manage Kubernetes clusters that power GPU-accelerated computer-vision workloads in both public cloud and on-prem customer sites.Design and own zero-touch deployment pipelines that support blue/green, canary, and instant rollback strategies for over-the-air updates.Codify infrastructure with Terraform, Helm, and similar tools so every environment spins up the same way every time.Embed scalable observability with Prometheus, Grafana, and OpenTelemetry to surface fleet health and performance insights in real time.Partner with SRE and software teams to deliver resilient, easy-to-deploy microservices and APIs.Lead post-incident reviews, driving systemic fixes that strengthen reliability release after release.Champion security best practices around identity, secrets management, and network segmentation across cloud and edge footprints.
What You Bring5+ years in DevOps, Platform, or Site Reliability Engineering.Hands-on experience running Kubernetes in production and troubleshooting containerized workloads.Proficiency with Infrastructure-as-Code (Terraform, Helm, Ansible, or equivalents).Strong scripting or development skills in Python, Go, or a comparable language.Deep Linux knowledge plus solid fundamentals in networking and performance tuning.Practical experience with CI/CD pipelines (GitHub Actions, GitLab CI, Jenkins, etc.).Exposure to distributed or hybrid cloud/edge systems; GPU scheduling or industrial IoT is a plus.Clear, collaborative communication style and a bias for owning problems end-to-end.
About Blue Signal: Blue Signal is an award-winning, executive search firm specializing in various specialties. Our recruiters have a proven track record of placing top-tier talent across industry verticals, with deep expertise in numerous professional services. Learn more at bit.ly/46Gs4yS
DevOps EngineerLocation: Remote (Canada-wide) with preference for applicants in the Greater Toronto Area
About the CompanyOur client is a confidential, venture-backed pioneer at the intersection of AI, computer vision, and industrial automation. Their edge-focused platform is already improving safety and efficiency on factory floors across North America, and they are scaling fast.
Why This Role RocksBuild a green-field infrastructure layer that bridges cloud and edge for thousands of devices.Work in a fully remote, senior-only engineering culture that values autonomy and rapid iteration.See your work ship to real machines—impact measured in uptime, not vanity metrics.Competitive salary, meaningful early-stage equity, and first-class benefits.
Compensation & BenefitsMarket-competitive base pay plus meaningful equity.Flexible hours, 100 percent remote setup, and an annual home-office stipend.Comprehensive health, dental, vision, and mental-health coverage.Generous PTO, quarterly recharge Fridays, and a professional development budget.
Key ResponsibilitiesEngineer and automate the cloud-plus-edge backbone that keeps thousands of Linux-based devices online, healthy, and secure.Manage Kubernetes clusters that power GPU-accelerated computer-vision workloads in both public cloud and on-prem customer sites.Design and own zero-touch deployment pipelines that support blue/green, canary, and instant rollback strategies for over-the-air updates.Codify infrastructure with Terraform, Helm, and similar tools so every environment spins up the same way every time.Embed scalable observability with Prometheus, Grafana, and OpenTelemetry to surface fleet health and performance insights in real time.Partner with SRE and software teams to deliver resilient, easy-to-deploy microservices and APIs.Lead post-incident reviews, driving systemic fixes that strengthen reliability release after release.Champion security best practices around identity, secrets management, and network segmentation across cloud and edge footprints.
What You Bring5+ years in DevOps, Platform, or Site Reliability Engineering.Hands-on experience running Kubernetes in production and troubleshooting containerized workloads.Proficiency with Infrastructure-as-Code (Terraform, Helm, Ansible, or equivalents).Strong scripting or development skills in Python, Go, or a comparable language.Deep Linux knowledge plus solid fundamentals in networking and performance tuning.Practical experience with CI/CD pipelines (GitHub Actions, GitLab CI, Jenkins, etc.).Exposure to distributed or hybrid cloud/edge systems; GPU scheduling or industrial IoT is a plus.Clear, collaborative communication style and a bias for owning problems end-to-end.
About Blue Signal: Blue Signal is an award-winning, executive search firm specializing in various specialties. Our recruiters have a proven track record of placing top-tier talent across industry verticals, with deep expertise in numerous professional services. Learn more at bit.ly/46Gs4yS
DevOps EngineerLocation: Remote (Canada-wide) with preference for applicants in the Greater Toronto Area
About the CompanyOur client is a confidential, venture-backed pioneer at the intersection of AI, computer vision, and industrial automation. Their edge-focused platform is already improving safety and efficiency on factory floors across North America, and they are scaling fast.
Why This Role RocksBuild a green-field infrastructure layer that bridges cloud and edge for thousands of devices.Work in a fully remote, senior-only engineering culture that values autonomy and rapid iteration.See your work ship to real machines—impact measured in uptime, not vanity metrics.Competitive salary, meaningful early-stage equity, and first-class benefits.
Compensation & BenefitsMarket-competitive base pay plus meaningful equity.Flexible hours, 100 percent remote setup, and an annual home-office stipend.Comprehensive health, dental, vision, and mental-health coverage.Generous PTO, quarterly recharge Fridays, and a professional development budget.
Key ResponsibilitiesEngineer and automate the cloud-plus-edge backbone that keeps thousands of Linux-based devices online, healthy, and secure.Manage Kubernetes clusters that power GPU-accelerated computer-vision workloads in both public cloud and on-prem customer sites.Design and own zero-touch deployment pipelines that support blue/green, canary, and instant rollback strategies for over-the-air updates.Codify infrastructure with Terraform, Helm, and similar tools so every environment spins up the same way every time.Embed scalable observability with Prometheus, Grafana, and OpenTelemetry to surface fleet health and performance insights in real time.Partner with SRE and software teams to deliver resilient, easy-to-deploy microservices and APIs.Lead post-incident reviews, driving systemic fixes that strengthen reliability release after release.Champion security best practices around identity, secrets management, and network segmentation across cloud and edge footprints.
What You Bring5+ years in DevOps, Platform, or Site Reliability Engineering.Hands-on experience running Kubernetes in production and troubleshooting containerized workloads.Proficiency with Infrastructure-as-Code (Terraform, Helm, Ansible, or equivalents).Strong scripting or development skills in Python, Go, or a comparable language.Deep Linux knowledge plus solid fundamentals in networking and performance tuning.Practical experience with CI/CD pipelines (GitHub Actions, GitLab CI, Jenkins, etc.).Exposure to distributed or hybrid cloud/edge systems; GPU scheduling or industrial IoT is a plus.Clear, collaborative communication style and a bias for owning problems end-to-end.
About Blue Signal: Blue Signal is an award-winning, executive search firm specializing in various specialties. Our recruiters have a proven track record of placing top-tier talent across industry verticals, with deep expertise in numerous professional services. Learn more at bit.ly/46Gs4yS
DevOps EngineerLocation: Remote (Canada-wide) with preference for applicants in the Greater Toronto Area
About the CompanyOur client is a confidential, venture-backed pioneer at the intersection of AI, computer vision, and industrial automation. Their edge-focused platform is already improving safety and efficiency on factory floors across North America, and they are scaling fast.
Why This Role RocksBuild a green-field infrastructure layer that bridges cloud and edge for thousands of devices.Work in a fully remote, senior-only engineering culture that values autonomy and rapid iteration.See your work ship to real machines—impact measured in uptime, not vanity metrics.Competitive salary, meaningful early-stage equity, and first-class benefits.
Compensation & BenefitsMarket-competitive base pay plus meaningful equity.Flexible hours, 100 percent remote setup, and an annual home-office stipend.Comprehensive health, dental, vision, and mental-health coverage.Generous PTO, quarterly recharge Fridays, and a professional development budget.
Key ResponsibilitiesEngineer and automate the cloud-plus-edge backbone that keeps thousands of Linux-based devices online, healthy, and secure.Manage Kubernetes clusters that power GPU-accelerated computer-vision workloads in both public cloud and on-prem customer sites.Design and own zero-touch deployment pipelines that support blue/green, canary, and instant rollback strategies for over-the-air updates.Codify infrastructure with Terraform, Helm, and similar tools so every environment spins up the same way every time.Embed scalable observability with Prometheus, Grafana, and OpenTelemetry to surface fleet health and performance insights in real time.Partner with SRE and software teams to deliver resilient, easy-to-deploy microservices and APIs.Lead post-incident reviews, driving systemic fixes that strengthen reliability release after release.Champion security best practices around identity, secrets management, and network segmentation across cloud and edge footprints.
What You Bring5+ years in DevOps, Platform, or Site Reliability Engineering.Hands-on experience running Kubernetes in production and troubleshooting containerized workloads.Proficiency with Infrastructure-as-Code (Terraform, Helm, Ansible, or equivalents).Strong scripting or development skills in Python, Go, or a comparable language.Deep Linux knowledge plus solid fundamentals in networking and performance tuning.Practical experience with CI/CD pipelines (GitHub Actions, GitLab CI, Jenkins, etc.).Exposure to distributed or hybrid cloud/edge systems; GPU scheduling or industrial IoT is a plus.Clear, collaborative communication style and a bias for owning problems end-to-end.
About Blue Signal: Blue Signal is an award-winning, executive search firm specializing in various specialties. Our recruiters have a proven track record of placing top-tier talent across industry verticals, with deep expertise in numerous professional services. Learn more at bit.ly/46Gs4yS
