IT Operations Lead
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IT Operations Lead at Mind Robotics, Palo Alto (On-site). Posted Sep 8, 2026, last seen on the employer's hiring page Nov 5, 2026.
About the team and the role Mind Robotics is building intelligent robotic systems. Our work happens on-site across active hardware labs, test floors, and compute environments where hardware and software iterate together daily. As our first dedicated IT hire, you will build and own our IT operations...
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About the team and the role
Mind Robotics is building intelligent robotic systems. Our work happens on-site across active hardware labs, test floors, and compute environments where hardware and software iterate together daily.
As our first dedicated IT hire, you will build and own our IT operations end to end. You’ll be responsible for making sure our teams never lose momentum to tooling, identity, device, or network issues, whether that means troubleshooting a Linux/driver setup in the lab, setting up zero-touch laptop provisioning for new hires, or ensuring our test-floor Wi-Fi can handle high-throughput robot telemetry.
We believe modern IT should be built for extreme leverage. In this role, you will actively use AI agents and build agentic workflows (leveraging LLMs, MCP, and API integrations) to automate support intake, triage, provisioning, access approvals, and system reconciliation. You'll build an AI-native IT foundation that keeps operations fast, lean, and scalable without scaling support headcount.
Responsibilities
Own internal IT & support: Be the primary technical point of contact for the team. Establish a lightweight, responsive support workflow that unblocks engineers quickly without unnecessary red tape.
Build agentic automations & workflows: Leverage AI coding agents and LLM-driven workflows (via APIs, MCP, webhooks) to automate repetitive IT operations: such as intelligent ticket triage, access requests, onboarding/off-boarding, and system reconciliation.
Manage identity, access, and endpoints: Administer our core SaaS, identity, and access stack (Google Workspace / IdP) and deploy modern MDM (e.g., Fleet, Jamf) for zero-touch provisioning and fleet visibility across macOS, Windows, and Linux machines.
Support robotics lab & compute infrastructure: Help maintain our lab workstation fleet (Ubuntu boxes, test bench PCs), keeping configurations reliable and reproducible.
Design and maintain office & lab networking: Manage local network infrastructure - VLAN segmentation (isolating robot telemetry, test benches, and corporate traffic), Wi-Fi reliability in dense RF lab environments, managed switches, and ISP circuits.
Manage hardware & procurement: Own hardware ordering, inventory tracking, vendor relationships, conference room AV, and hands-on physical lab IT setup (racking, cabling, and workstation rollouts).
Requirements
Experience: 6+ years of hands-on IT operations, systems administration, or IT engineering experience, ideally in a fast-paced startup, hardware, or robotics environment.
AI & Agentic fluency: Active user of AI coding tools and agents (Cursor, Claude Code, LLM APIs) to accelerate development, with experience or strong interest in building agentic/LLM-assisted workflows for operations.
Multi-OS troubleshooting: Strong troubleshooting skills across macOS, Windows, and Linux (Ubuntu) at the OS, driver, and application layers.
Networking fundamentals: Practical hands-on experience configuring managed switches, subnets, VLANs, DNS/DHCP, VPN, and robust Wi-Fi networks.
AI & MCP integrations: Experience deploying LLM agents, MCP servers, or AI-native internal tools using Python, JS, Git, or Bash for IT/Ops automation.
Identity & MDM: Hands-on experience administering enterprise identity (Google Workspace, Okta) and modern MDM platforms (Fleet, Jamf, Intune, or equivalent).
Hands-on facility readiness: Willingness to work on-site and handle physical infrastructure: racking equipment, running and terminating cable, and supporting all types of hardware in an active lab and office environment.
Robotics & ML: Experience supporting robotics environments, ROS, or GPU/CUDA machine learning workstations (is a plus).
Facility scaling: Experience managing IT infrastructure through a new facility buildout or office/lab move (is a plus).
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