Senior Backend Engineer - Virtual Guard

Verkada · Enterprise · Bayoffice · Alarms

Senior Backend Engineer role focused on building and scaling backend systems for AI-driven physical security products. The role involves designing infrastructure for automated intrusion detection, real-time decisioning, and intelligent response systems, processing multimodal data (video, audio, sensors) across cloud and edge environments. Key responsibilities include developing scalable data pipelines, architecting event-driven systems, building infrastructure for ML model integration, and optimizing for low latency and high availability.

What you'd actually do

  1. Design and build distributed backend systems that power AI-driven detection, monitoring, and response workflows
  2. Develop scalable pipelines for ingesting and processing large volumes of video, audio, and sensor data in real time
  3. Architect event-driven systems that trigger automated actions such as alerts, verification, and escalation
  4. Build infrastructure that enables integration and deployment of large video and audio models into production systems
  5. Rapidly prototype and iterate on new AI-powered capabilities, moving from concept to deployed features

Skills

Required

  • 5+ years of backend engineering experience building and operating production systems at scale
  • Strong experience designing distributed systems, event-driven architectures, and scalable APIs
  • Proven track record of building large-scale, data-intensive or AI-powered systems
  • Experience working with real-time data pipelines and high-throughput systems
  • Familiarity with deploying or integrating machine learning models, especially in video, audio, or multimodal domains
  • Strong programming skills (e.g., Go, Python)
  • Experience with modern cloud infrastructure
  • Experience with databases and streaming systems (e.g., Kafka, Temporal, Postgres)
  • Ability to quickly prototype, experiment, and iterate in ambiguous problem spaces
  • Strong ownership mindset with experience delivering reliable, production-grade systems end-to-end

What the JD emphasized

  • building and operating production systems at scale
  • building large-scale, data-intensive or AI-powered systems
  • deploying or integrating machine learning models, especially in video, audio, or multimodal domains
  • low latency
  • high availability
  • reliability

Other signals

  • building backend systems for AI-driven physical security products
  • designing infrastructure and workflows for automated intrusion detection and real-time decisioning
  • owning architecture for large-scale, low-latency systems processing multimodal data
  • integrating and deploying machine learning models, especially in video, audio, or multimodal domains