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Trigo’s AI-powered platform is deployed across dozens of autonomous and mainstream retail stores —and that number is growing fast. Ensuring these systems are deployed reliably and run flawlessly requires a world-class operations technology backbone.

We’re looking for a Director of Operations Technology to lead this function end-to-end. You’ll oversee a team responsible for technology deployment, production stability, and support—including DevOps, SRE, System Engineering, ML Ops, and the NOC team. Your focus will span the full lifecycle: from remote deployment and configuration, to ongoing performance monitoring and issue resolution across live customer environments.

You’ll also serve as a senior technical voice in complex customer-facing scenarios—advising on integration readiness, infrastructure architecture, and system behavior when needed.

This is a high-impact leadership role that combines technical depth, operational ownership, and a clear understanding of what it takes to support complex AI systems in real-world retail environments.

• Lead Trigo’s Operations Technology group, covering deployment engineering, production support, and system reliability
• Oversee the full tech deployment lifecycle, from infrastructure bring-up to service orchestration and ML model rollout
• Ensure production uptime, observability, and rapid incident resolution across all live stores
• Manage the NOC function through its dedicated team leader, owning all levels of production support
• Drive automation, tooling, and standardization to enable reliable, scalable deployments
• Collaborate with R&D and Product to ensure new features are deployment-ready and supportable
• Represent the technology organization in high-stakes, customer-facing technical discussions when needed
• Own KPIs around deployment velocity, system uptime, and issue resolution
• Lead one of Trigo’s most critical technical functions as we scale globally
• Own the systems that bring AI to life—store by store, hour by hour
• Work across infrastructure, reliability, and real-world execution
• Influence how we build, deploy, and support the future of in-store AI

• Experience in edge computing, retail tech, or computer vision systems
• Familiarity with tools like Kubernetes, Octopus Deploy, Prometheus, Terraform, Grafana
• Exposure to live operations or customer integration work in production AI/ML systems