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Berry AI

AI-powered QSR speed-of-service analytics

System Team Lead

Engineering LeadershipConfirmed live in the last 24 hours
Full-timeTaipei City, TaiwanNo salary listed

About the Job

Requirements

  • A track record of leading an infrastructure, platform, or site reliability engineering team while remaining hands-on in systems work.
  • At least 5 years of experience in systems, infrastructure, or DevOps engineering, with strong Linux (Ubuntu) administration and experience operating fleets at scale.
  • Strong networking fundamentals, including TCP/IP, DNS, VLANs, VPNs, and firewalls.
  • Deep infrastructure-as-code, configuration-management, and orchestration experience across on-premises and cloud environments, such as Terraform or Pulumi.
  • Observability experience running metrics, logs, and alerting at scale, defining service-level objectives, and balancing monitoring detail against storage and cost.
  • Solid automation and scripting skills, especially Bash and Python; Go is also useful.
  • Fluent Mandarin and English; Mandarin is the team's working language, and fluent English is required for daily work with US teams, customers, and IT vendors.
  • A pragmatic sense of ownership, balancing reliability against delivery velocity and prioritizing problems to solve.

Responsibilities

  • Lead and grow the system team, set technical direction, mentor engineers, own hiring, and remain hands-on.
  • Own the on-premises edge fleet of in-store servers and cameras across customer networks, reached through resilient VPN/mesh paths using OpenVPN and Tailscale.
  • Build internal tools, scripts, and APIs that enable the customer success team and on-site technicians to install and troubleshoot store servers, networks, and cameras independently, converting cross-team escalations into self-service fixes.
  • Own the self-hosted observability platform across edge and cloud, using a Prometheus-ecosystem stack including Grafana, Mimir, Loki, VMAgent, and Vector, with service-level-objective dashboards and alerting feeding automated ticketing and remediation.
  • Drive automation to keep operational load flat as the fleet grows, including event-driven auto-ticketing and auto-remediation across Ansible/AWX and serverless AWS services (SNS, SQS, and Lambda).
  • Run core infrastructure and services at the Taipei headquarters, including servers and office networking, virtualization, Kubernetes, storage, device monitoring, and self-hosted services such as a container registry, authentication, and reverse proxy.
  • Steer the roadmap so systems work enables product velocity, partnering with machine learning engineers, product managers, customer success, customers, and customer-side IT.
  • Run the on-call rotation, lead incident response, and turn recurring issues into durable fixes and runbooks.
  • Own security and compliance operations, including the ISO 27001 information security management system, vulnerability management, code security scanning, and disaster-recovery drills.

Desired Qualifications

  • Familiarity with IP cameras/NVRs and the ONVIF protocol, plus real-time video streaming using RTSP, H.264/H.265, or MediaMTX.
  • Experience with storage and NAS operations at scale, including ZFS/TrueNAS, Synology, QNAP, and RAID/HA.
  • Hands-on vulnerability management and static application security testing, such as OpenVAS or SonarQube.
  • Experience with workflow-automation tooling such as n8n and building low-toil operational systems.
  • Familiarity with modern AI tooling, including large language models, coding agents, and agent-driven workflows.

About the Company

Berry AI

AI-powered QSR speed-of-service analytics

Berry AI provides affordable technology for quick-service restaurants to improve Speed of Service by revealing how long customers spend in line and how many abandon before ordering. Its product collects and analyzes data on customer flow and service times to generate clear metrics and recommendations that operators can act on. Unlike some competitors, Berry AI emphasizes practical, low-cost insights that directly impact revenue and offers scalable, brand-wide analytics across the full customer journey. The company’s goal is to help QSR operators maximize throughput and profitability by turning in-line time and abandonment data into actionable improvements.

Company size
11-50
Company stage
Not listed
Total funding
Not listed
Headquarters
Not listed
Founded
Not listed

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