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Mind Robotics is seeking its first dedicated IT Operations Lead to build and own end-to-end IT operations for a hardware-focused robotics company. You will be the primary technical point of contact for engineering teams, responsible for ensuring seamless operations across active hardware labs, test floors, and compute environments.
Key responsibilities include establishing lightweight, responsive IT support workflows; building AI-native agentic automations to handle ticket triage, access requests, onboarding/offboarding, and system reconciliation; administering identity and access management (Google Workspace, IdP); deploying modern MDM solutions (Fleet, Jamf) for zero-touch provisioning across macOS, Windows, and Linux; maintaining lab workstation fleets (Ubuntu boxes, test benches); designing and managing office and lab networking infrastructure including VLAN segmentation, Wi-Fi reliability in RF-dense environments, managed switches, and ISP circuits; and owning hardware procurement, inventory tracking, vendor relationships, and hands-on physical lab setup (racking, cabling, workstation rollouts).
You will actively leverage AI agents and LLM-driven workflows (via APIs, MCP, webhooks) to automate repetitive IT operations and build an AI-native IT foundation that keeps operations fast, lean, and scalable without proportional headcount growth.
Required qualifications: 6+ years of hands-on IT operations, systems administration, or IT engineering experience, ideally in a fast-paced startup or hardware environment; active proficiency with AI coding tools and agents (Cursor, Claude Code, LLM APIs); strong multi-OS troubleshooting across macOS, Windows, and Linux at OS, driver, and application layers; practical networking experience with managed switches, subnets, VLANs, DNS/DHCP, VPN, and Wi-Fi; experience deploying LLM agents or MCP servers using Python, JavaScript, Git, or Bash for IT/Ops automation; hands-on enterprise identity administration (Google Workspace, Okta) and modern MDM platforms (Fleet, Jamf, Intune); willingness to work on-site and handle physical infrastructure including racking, cabling, and hardware support in active lab and office environments.
Preferred: experience supporting robotics environments, ROS, or GPU/CUDA machine learning workstations; experience managing IT infrastructure through facility buildouts or office/lab moves.
